Items of some interest:

These are my recent Pin​board​.in links:

  • pry/​pry

    Pry is a pow­er­ful alter­na­tive to the stan­dard IRB shell for Ruby. It is writ­ten from scratch to pro­vide a num­ber of advanced fea­tures, including:

    irb ruby software-​​development inter­preter
  • Daniel Fischer’s Blog — A Start­ing Guide to VIM from Textmate

    For about four years I’ve been using Text­mate almost every day. I’m very fast with it. I’ve always thought about switch­ing over to VIM or Emacs but I have been scared of los­ing my speed. In fact, I’ve actu­ally tried Emacs in the past and also wrote a blog post on my expe­ri­ence. I liked it in gen­eral, but I ended up com­ing back to Text­mate after a week. Why? I didn’t really feel like I was gain­ing anything.

    text­mate vim tuto­r­ial habit
  • A Ques­tion Answered — Credit Slips

    “Over cof­fee this morn­ing with a friend, I threw out the same ques­tion from my orig­i­nal post. How does an orga­ni­za­tion get itself to the place where it col­lec­tively comes to think such strong-​​arm col­lec­tion tac­tics on hos­pi­tal patients are a good idea, let alone morally defen­si­ble? A pro­file of Accretive’s CEO, Mary Tolan, in Crain’s Chicago Busi­ness con­tains this gem: “My objec­tive is just to be a happy, con­fi­dent cap­i­tal­ist,” says the devo­tee of Ayn Rand’s and Mil­ton Friedman’s free-​​market gospel, which she applies with a com­bat­ive, survival-​​of-​​the fittest man­age­ment style.”

    ran­dism buh-​​bye-​​john-​​galt
  • The Hum­ble Ori­gins of the NEXT Global Econ­omy. Don’t Miss Out.

    “It’s sim­ple.  If you want to build a thriv­ing local econ­omy.  A local econ­omy that makes your com­mu­nity resilient to eco­nomic fail­ure and shocks, you need to find ways to help the inno­va­tors in your com­mu­nity make things.”

    resilience sus­tain­abil­ity communities-​​of-​​practice mak­ers

Items of some interest:

These are my recent Pin​board​.in links:

  • BOOKTRYST: Amer­i­can Rare Book Trade Ads From 1902

    ‘Where to begin with Charles Car­ring­ton (b. 1867 — d. 1921 of syphilis), who deserves an entire book devoted to his col­or­ful char­ac­ter and career? Of Por­tuguese descent, Car­ring­ton,  born Paul Harry Fer­nandino, was, arguably, the most noto­ri­ous pub­lisher of his gen­er­a­tion. He began in Lon­don. Circa 1893–96 he skipped to Paris; deported from France in 1907, he fled to Brus­sels. In 1912, he returned to Paris, at times Ams­ter­dam. In short, he oper­ated one step ahead of the law. “His­tor­i­cal, Artis­tic, Med­ical, and Anthro­po­log­i­cal Works,” is cer­tainly one way to char­ac­ter­ize the books he pub­lished. Erot­ica, pornog­ra­phy, curiosa, and sex­ol­ogy are other appro­pri­ate descrip­tions. Often, the stated pub­li­ca­tion locale, pub­lisher, and date on his books were false. Many if not most of his books were “for pri­vate sub­scribers only.” He was active as a pub­lisher for twenty-​​six years and pub­lished approx­i­mately 300 books.’

    book­seller bib­lio­ma­nia nanohis­tory characters-​​we-​​have-​​been-​​like

  • The Ongo­ing Vigil of Soft­ware Security

    “Some of the rea­sons that we keep see­ing these types of exploits are that the “bad guys” are much smarter and more deter­mined than we give them credit for, we’re much lazier and more igno­rant than we take respon­si­bil­ity for, and secu­rity is dif­fi­cult to man­age prop­erly. As we become more and more reliant upon soft­ware, it is imper­a­tive that secu­rity be taken more seriously.”

    software-​​development secu­rity advice overview

  • Economist’s View: “The Soci­ol­ogy of Organizations”

    “It often sounds as though Per­row is fault­ing these orga­ni­za­tions for defects that are inher­ent in all large orga­ni­za­tions. But it seems more fair to say that his analy­sis does not iden­tify a gen­eral fea­ture of orga­ni­za­tions that leads to fail­ure in these cases, but rather a sit­u­a­tional fact hav­ing to do with the power of busi­ness to resist reg­u­la­tion and the sus­cep­ti­bil­ity of Con­gress and the Pres­i­dent to polit­i­cal pres­sures that ham­string effec­tive reg­u­la­tory orga­ni­za­tions. Per­row does refer to spe­cific orga­ni­za­tional haz­ards — bad exec­u­tive lead­er­ship, fal­ter­ing morale, inabil­ity to col­lab­o­rate across agen­cies, exces­sively hier­ar­chi­cal archi­tec­ture — but the heart of his argu­ment lies else­where. The key set of prob­lems spi­ral back to the inor­di­nate power that cor­po­ra­tions have in the United States, and the dis­tor­tions they cre­ate in Con­gress and the exec­u­tive branch. … It is specifics of the US polit­i­cal sys­tem rather than gen­eral defects of large orga­ni­za­tions per se that lead to the bad out­comes that Per­row iden­ti­fies. There are strong democ­ra­cies that do a much bet­ter job of reg­u­lat­ing risky indus­tries and plan­ning for dis­as­ters than we do — for exam­ple, France and Ger­many. …
    There isn’t much pub­lic con­cern about these risks, and leg­is­la­tors are there­fore free to ignore them as well. … So where will the polit­i­cal demand for strong reg­u­la­tion come from? Will we need to wait for the bad news we’ve man­aged by good for­tune to have avoided up to this point?”

    public-​​policy infra­struc­ture antebellum-​​America con­ser­vatism

  • Bach­mann, Gaffney, and the GOP’s Anti-​​Muslim Cul­ture of Con­spir­acy — The Daily Beast

    “Ear­lier this month, Rep. Louie Gohmert (R-​​TX) appeared on the FOX Busi­ness show Money Rocks to make the case for depriv­ing the chil­dren of immi­grants of their 14th Amend­ment rights. Gohmert claimed that on a recent air­plane trip to the Mid­dle East, one of his trav­el­ing com­pan­ions had struck up a con­ver­sa­tion with a grand­mother who described her family’s involve­ment in a Hamas plot to send preg­nant women to the United States. Gohmert sum­ma­rized the les­son for view­ers this way: “We’re bring­ing them over here on tourist visas, some ille­gally, let­ting them be born here and say­ing, ‘This is an Amer­i­can cit­i­zen. So come back in 20, 25 years when you’re ready to blow us up.’””

    para­noia Repub­li­cans con­ser­vatism conspiracy-​​theories political-​​discourse antebellum-​​America

Items of some interest:

These are my recent Pin​board​.in links:

  • [1206.6866] Sto­chas­tic Opti­mal Con­trol in Con­tin­u­ous Space-​​Time Multi-​​Agent Systems

    “Recently, a the­ory for sto­chas­tic opti­mal con­trol in non-​​linear dynam­i­cal sys­tems in con­tin­u­ous space-​​time has been devel­oped (Kap­pen, 2005). We apply this the­ory to col­lab­o­ra­tive multi-​​agent sys­tems. The agents evolve accord­ing to a given non-​​linear dynam­ics with addi­tive Wiener noise. Each agent can con­trol its own dynam­ics. The goal is to min­i­mize the accu­mu­lated joint cost, which con­sists of a state depen­dent term and a term that is qua­dratic in the con­trol. We focus on sys­tems of non-​​interacting agents that have to dis­trib­ute them­selves opti­mally over a num­ber of tar­gets, given a set of end-​​costs for the dif­fer­ent pos­si­ble agent-​​target com­bi­na­tions. We show that opti­mal con­trol is the com­bi­na­to­r­ial sum of inde­pen­dent single-​​agent single-​​target opti­mal con­trols weighted by a fac­tor pro­por­tional to the end-​​costs of the dif­fer­ent com­bi­na­tions. Thus, multi-​​agent con­trol is related to a stan­dard graph­i­cal model infer­ence prob­lem. The addi­tional com­pu­ta­tional cost com­pared to single-​​agent con­trol is expo­nen­tial in the tree-​​width of the graph spec­i­fy­ing the com­bi­na­to­r­ial sum times the num­ber of tar­gets. We illus­trate the result by sim­u­la­tions of sys­tems with up to 42 agents.”

    coor­di­na­tion agent-​​based emergent-​​design nudge-​​targets control-​​theory
  • [1205.6917] Robust self-​​triggered coor­di­na­tion with ternary controllers

    “This paper regards coor­di­na­tion of net­worked sys­tems, which is stud­ied in the frame­work of hybrid dynam­i­cal sys­tems. We design a coor­di­na­tion scheme which com­bines the use of ternary con­trollers with a self-​​triggered com­mu­ni­ca­tion pol­icy. The com­mu­ni­ca­tion pol­icy requires the agents to col­lect, at each sam­pling time, rel­a­tive mea­sure­ments of their neigh­bors’ states: the col­lected infor­ma­tion is then used to update the con­trol and deter­mine the fol­low­ing sam­pling time. We prove that the pro­posed scheme ensures finite-​​time con­ver­gence to a neigh­bor­hood of a con­sen­sus state. We then study the robust­ness of the pro­posed self-​​triggered coor­di­na­tion sys­tem with respect to skews in the agents’ local clocks, to delays, and to lim­ited pre­ci­sion in com­mu­ni­ca­tion. Fur­ther­more, we present two sig­nif­i­cant vari­a­tions of our scheme. First, we design a time-​​varying con­troller which asymp­tot­i­cally dri­ves the sys­tem to con­sen­sus. Sec­ond, we adapt our frame­work to a com­mu­ni­ca­tion model in which an agent does not poll all its neigh­bors simul­ta­ne­ously, but sin­gle neigh­bors instead. This com­mu­ni­ca­tion pol­icy actu­ally leads to a self-​​triggered “gos­sip” coor­di­na­tion system.”

    network-​​theory multi-​​agent-​​systems mechanism-​​design emergent-​​design consensus-​​systems nudge-​​targets algo­rithms
  • [1205.2607] Simulation-​​Based Game The­o­retic Analy­sis of Key­word Auc­tions with Low-​​Dimensional Bid­ding Strategies

    “We per­form a simulation-​​based analy­sis of key­word auc­tions mod­eled as one-​​shot games of incom­plete infor­ma­tion to study a series of mech­a­nism design ques­tions. Our first ques­tion addresses the degree to which incen­tive com­pat­i­bil­ity fails in gen­er­al­ized second-​​price (GSP) auc­tions. Our results sug­gest that sin­cere bid­ding in GSP auc­tions is a strik­ingly poor strat­egy and a poor pre­dic­tor of equi­lib­rium out­comes. We next show that the rank-​​by-​​revenue mech­a­nism is wel­fare opti­mal, cor­rob­o­rat­ing past results. Finally, we ana­lyze profit as a func­tion of auc­tion mech­a­nism under a series of alter­na­tive set­tings. Our con­clu­sions coin­cide with those of Lahaie and Pen­nock [2007] when val­ues and qual­ity scores are strongly pos­i­tively cor­re­lated: in such a case, rank-​​by-​​bid rules are clearly supe­rior. We diverge, how­ever, in show­ing that auc­tions that put lit­tle weight on qual­ity scores almost uni­ver­sally dom­i­nate the pure rank-​​by-​​revenue scheme.”

    game-​​theory agent-​​based sim­u­la­tion eco­nom­ics auc­tion nudge-​​targets
  • Graph­ing the his­tory of phi­los­o­phy « Drunks&Lampposts

    “Each philoso­pher is a node in the net­work and the lines between them (or edges in the ter­mi­nol­ogy of graph the­ory) rep­re­sents lines of influ­ence. The node and text are sized accord­ing to the num­ber of con­nec­tions (both in and out). The algo­rithm that visu­alises the graph also tends to put the bet­ter con­nected nodes in the cen­tre of the dia­gram so we see the most influ­en­tial philoso­phers, in large text, clus­tered in the cen­tre. It all seems about right with the major fig­ures in the west­ern philo­soph­i­cal tra­di­tion tak­ing the cen­tre stage. (I need to also add the direc­tion of influ­ence with a arrow head – some­thing I’ve not got round to yet.) A short­com­ing how­ever is that this eval­u­a­tion only takes into account direct lines of influ­ence. Indi­rect influ­ence via another per­son in the net­work does not enter into it. This prob­a­bly explains why Descartes is smaller than you’d think. It would also be bet­ter if the nodes were sized only by the num­ber of out­ward con­nec­tions although I think over­all the dif­fer­ences would be slight. I’ll get round to that.”

    visu­al­iza­tion philosopher-​​mining
  • [1206.3666] Unsu­per­vised adap­ta­tion of brain machine inter­face decoders

    “The per­for­mance of neural decoders can degrade over time due to non­sta­tion­ar­i­ties in the rela­tion­ship between neu­ronal activ­ity and behav­ior. In this case, brain-​​machine inter­faces (BMI) require adap­ta­tion of their decoders to main­tain high per­for­mance across time. One way to achieve this is by use of peri­od­i­cal cal­i­bra­tion phases, dur­ing which the BMI sys­tem (or an exter­nal human demon­stra­tor) instructs the user to per­form cer­tain move­ments or behav­iors. This approach has two dis­ad­van­tages: (i) cal­i­bra­tion phases inter­rupt the autonomous oper­a­tion of the BMI and (ii) between two cal­i­bra­tion phases the BMI per­for­mance might not be sta­ble but con­tin­u­ously decrease. A bet­ter alter­na­tive would be that the BMI decoder is able to con­tin­u­ously adapt in an unsu­per­vised man­ner dur­ing autonomous BMI oper­a­tion, i.e. with­out know­ing the move­ment inten­tions of the user. In the present arti­cle, we present an effi­cient method for such unsu­per­vised train­ing of BMI sys­tems for con­tin­u­ous move­ment con­trol. The pro­posed method uti­lizes a cost func­tion derived from neu­ronal record­ings, which guides a learn­ing algo­rithm to eval­u­ate the decod­ing para­me­ters. We ver­ify the per­for­mance of our adap­tive method by sim­u­lat­ing a BMI user with an opti­mal feed­back con­trol model and its inter­ac­tion with our adap­tive BMI decoder. The sim­u­la­tion results show that the cost func­tion and the algo­rithm yield fast and pre­cise tra­jec­to­ries towards tar­gets at ran­dom ori­en­ta­tions on a 2-​​dimensional com­puter screen. For ini­tially unknown and non-​​stationary tun­ing para­me­ters, our unsu­per­vised method is still able to gen­er­ate pre­cise tra­jec­to­ries and to keep its per­for­mance sta­ble in the long term. The algo­rithm can option­ally work also with neu­ronal error sig­nals instead or in con­junc­tion with the pro­posed unsu­per­vised adaptation.”

    FOR-​​SCIENCE brain-​​machine-​​interface user-​​interface adaptive-​​control emergent-​​design
  • [1206.3980] Visu­al­iz­ing Stream­ing Text Data with Dynamic Maps

    “The many end­less rivers of text now avail­able present a seri­ous chal­lenge in the task of glean­ing, ana­lyz­ing and dis­cov­er­ing use­ful infor­ma­tion. In this paper, we describe a method­ol­ogy for visu­al­iz­ing text streams in real time. The approach auto­mat­i­cally groups sim­i­lar mes­sages into “coun­tries,” with key­word sum­maries, using seman­tic analy­sis, graph clus­ter­ing and map gen­er­a­tion tech­niques. It han­dles the need for visual sta­bil­ity across time by dynamic graph lay­out and Pro­crustes pro­jec­tion tech­niques, enhanced with a novel sta­ble com­po­nent pack­ing algo­rithm. The result pro­vides a con­tin­u­ous, suc­cinct view of evolv­ing top­ics of inter­est. It can be used in pas­sive mode for overviews and sit­u­a­tional aware­ness, or as an inter­ac­tive data explo­ration tool. To make these ideas con­crete, we describe their appli­ca­tion to an online ser­vice called TwitterScope.”

    visu­al­iza­tion data algo­rithms user-​​experience
  • [1205.3352] Revis­it­ing the effect of exter­nal fields in Axelrod’s model of social dynamics

    “The study of the effects of spa­tially uni­form fields on the steady-​​state prop­er­ties of Axelrod’s model has yielded plenty of con­tro­ver­sial results. Here we re-​​examine the impact of this type of field for a selec­tion of para­me­ters such that the field-​​free steady state of the model is het­ero­ge­neous or mul­ti­cul­tural. Analy­ses of both one and two-​​dimensional ver­sions of Axelrod’s model indi­cate that, con­trary to pre­vi­ous claims in the lit­er­a­ture, the steady state remains het­ero­ge­neous regard­less of the value of the field strength. Turn­ing on the field leads to a dis­con­tin­u­ous decrease on the num­ber of cul­tural domains, which we argue is due to the insta­bil­ity of zero-​​field het­ero­ge­neous absorb­ing con­fig­u­ra­tions. We find, how­ever, that spa­tially nonuni­form fields that imple­ment a con­sen­sus rule among the neigh­bor­hood of the agents enforces homog­e­niza­tion. Although the over­all effects of the fields are essen­tially the same irre­spec­tive of the dimen­sion­al­ity of the model, we argue that the dimen­sion­al­ity has a sig­nif­i­cant impact on the sta­bil­ity of the field-​​free homo­ge­neous steady state.”

    com­plex­ol­ogy agent-​​based exter­nal­i­ties sim­u­la­tion evolutionary-​​economics nudge-​​targets
  • [1206.3421] Lin­ear Latent Vari­able Mod­els: The lava-​​package

    “An R pack­age for spec­i­fy­ing and esti­mat­ing lin­ear latent vari­able mod­els is pre­sented. The phi­los­o­phy of the imple­men­ta­tion is to sep­a­rate the model spec­i­fi­ca­tion from the actual data, which leads to a dynamic and easy way of mod­el­ing com­plex hier­ar­chi­cal struc­tures. Sev­eral advanced fea­tures are imple­mented includ­ing robust stan­dard errors for clus­tered cor­re­lated data, multi­group analy­ses, non-​​linear para­me­ter con­straints, infer­ence with incom­plete data, max­i­mum like­li­hood esti­ma­tion with cen­sored and binary obser­va­tions, and instru­men­tal vari­able esti­ma­tors. In addi­tion an exten­sive sim­u­la­tion inter­face cov­er­ing a broad range of non-​​linear gen­er­al­ized struc­tural equa­tion mod­els is described. The model and soft­ware are demon­strated in data of mea­sure­ments of the sero­tonin trans­porter in the human brain.”

    ontol­ogy sta­tis­tics algo­rithms R-​​language linear-​​models model-​​view-​​controller design-​​patterns
  • [1205.6129] The Miss­ing Mem­ris­tor: Novel Nan­otech­nol­ogy or rather new Case Study for the Phi­los­o­phy and Soci­ol­ogy of Science?

    “In 2008, it was widely announced that the miss­ing mem­ris­tor, a basic two-​​terminal elec­tri­cal cir­cuit ele­ment, had finally been dis­cov­ered. The mem­ris­tor is the fourth and last such cir­cuit ele­ment and thus com­pletes cir­cuit the­ory. Pre­dicted already in 1971, the even­tual dis­cov­ery of some­thing seem­ingly so basic needed almost 40 years. How­ever, this dis­cov­ery is doubted. The pre­dicted mem­ris­tor has no mate­r­ial mem­ory and is based on mag­netic flux, but the dis­cov­ered devices con­sti­tute ana­logue mem­ory stor­age that do not involve mag­net­ism. The per­son who orig­i­nally pro­posed the mem­ris­tor did not reject the dis­cov­ery but instead changed his mind about what a mem­ris­tor is. We briefly intro­duce the his­tory and then care­fully mem­ris­tance and the mem­ris­tor as such. We dis­cuss its sta­tus as a model rather than a device. We dis­cuss the dis­cov­ered devices, their sta­bil­ity, and how sta­bil­ity relates to the con­sis­tency of the the­o­ret­i­cal enti­ties. A thought exper­i­ment assumes a world with­out mag­net­ism. Induc­tors can­not exist there, but mem­ory resis­tors could still be con­structed. On the same grounds as the mem­ris­tor was his­tor­i­cally pre­dicted, an “induc­tor” could then be pre­dicted. Likely, some­body would also ‘dis­cover’ one. A ten­ta­tive soci­o­log­i­cal analy­sis com­pares to the flawed detec­tion of grav­i­ta­tional waves but comes to very dif­fer­ent conclusions.”

    symmetry-​​is-​​the-​​way-​​things-​​ought-​​to-​​be history-​​of-​​science technical-​​assumptions engineering-​​philosophy
  • [1205.2776] Trans­port on cou­pled spa­tial networks

    “Trans­port processes on spa­tial net­works are rep­re­sen­ta­tive of a broad class of real world sys­tems which, rather than being inde­pen­dent, are typ­i­cally inter­de­pen­dent. We pro­pose a mea­sure of util­ity to cap­ture key fea­tures that arise when such sys­tems are cou­pled together. The cou­pling is defined in a way that is not solely topo­log­i­cal, rely­ing on both the dis­tri­b­u­tion of sources and sinks, and the method of route assign­ment. Using a toy model, we explore rel­e­vant cases by sim­u­la­tion. For cer­tain para­me­ter val­ues, a pic­ture emerges of two regimes. The first occurs when the flows go from many sources to a small num­ber of sinks. In this case, net­work util­ity is largest when the cou­pling is at its max­i­mum and the aver­age short­est path is min­i­mized. The sec­ond regime arises when many sources cor­re­spond to many sinks. Here, the opti­mal cou­pling no longer cor­re­sponds to the min­i­mum aver­age short­est path, as the con­ges­tion of traf­fic must also be taken into account. More gen­er­ally, results indi­cate that cou­pled spa­tial sys­tems can give rise to behav­ior that relies sub­tly on the inter­play between the cou­pling and ran­dom­ness in the source-​​sink distribution.”

    nudge-​​targets network-​​theory emergent-​​design epi­demi­ol­ogy sim­u­la­tion
  • [1206.5849] Under­stand­ing the com­plex­ity of the L’evy-walk nature of human mobil­ity with a multi-​​scale cost/​benefit model

    “Prob­a­bil­ity dis­tri­b­u­tions of human dis­place­ments has been fit with expo­nen­tially trun­cated L’evy flights or fat tailed Pareto inverse power law prob­a­bil­ity dis­tri­b­u­tions. Thus, peo­ple usu­ally stay within a given loca­tion (for exam­ple, the city of res­i­dence), but with a non-​​vanishing fre­quency they visit nearby or far loca­tions too. Herein, we show that an impor­tant empir­i­cal dis­tri­b­u­tion of human dis­place­ments (range: from 1 to 1000 km) can be well fit by three con­sec­u­tive Pareto dis­tri­b­u­tions with sim­ple inte­ger expo­nents equal to 1, 2 and ($gtrap­prox$) 3. These three expo­nents cor­re­spond to three dis­place­ment range zones of about 1 km $less­sim Delta r less­sim$ 10 km, 10 km $less­sim Delta r less­sim$ 300 km and 300 km $less­sim Delta r less­sim $ 1000 km, respec­tively. These three zones can be geo­graph­i­cally and phys­i­cally well deter­mined as dis­place­ments within a city, vis­its to nearby cities that may occur within just one-​​day trips, and visit to far loca­tions that may require multi-​​days trips. The incre­men­tal inte­ger val­ues of the three expo­nents can be eas­ily explained with a three-​​scale mobil­ity cost/​benefit model for human dis­place­ments based on sim­ple geo­met­ri­cal con­strains. Essen­tially, peo­ple would divide the space into three major regions (close, medium and far dis­tances) and would assume that the travel ben­e­fits are randomly/​uniformly dis­trib­uted mostly only within spe­cific urban-​​like areas.”

    Levy-​​flights city-​​planning multiscale-​​phenomena self-​​similarity
  • [1206.7011] Ultra­thin Ter­a­hertz Pla­nar Lenses

    “Con­ven­tional opti­cal com­po­nents shape the wave­front of prop­a­gat­ing light by adjust­ing the opti­cal path length, which requires the use of rather thick lenses, espe­cially for the adjust­ment of ter­a­hertz (THz) radi­a­tion due to its long wave­length. Two ultra­thin THz pla­nar lenses were designed and fab­ri­cated based on inter­face phase mod­u­la­tion of antenna res­o­nance. The lens thick­nesses were extremely reduced to 100 nm, which is only 14000th of the illu­mi­nat­ing light wave­length. The focus­ing and imag­ing func­tions of the lenses were exper­i­men­tally demon­strated. The ultra­thin opti­cal com­po­nents described herein are a sig­nif­i­cant step toward the devel­op­ment of a micro-​​integrated THz system.”

    optics engineering-​​design nudge-​​targets
  • [1206.3789] Tree decom­po­si­tion and para­me­ter­ized algo­rithms for RNA structure-​​sequence align­ment includ­ing ter­tiary inter­ac­tions and pseudoknots

    “We present a gen­eral set­ting for structure-​​sequence com­par­i­son in a large class of RNA struc­tures that uni­fies and gen­er­al­izes a num­ber of recent works on spe­cific fam­i­lies on struc­tures. Our approach is based on tree decom­po­si­tion of struc­tures and gives rises to a gen­eral para­me­ter­ized algo­rithm, where the expo­nen­tial part of the com­plex­ity depends on the fam­ily of struc­tures. For each of the pre­vi­ously stud­ied fam­i­lies, our algo­rithm has the same com­plex­ity as the spe­cific algo­rithm that had been given before.”

    RNA structural-​​biology fold­ing bioin­for­mat­ics algo­rithms nudge-​​targets mod­el­ing
  • [1206.3403] Topo­log­i­cal Mea­sure Locat­ing the Effec­tive Crossover between Seg­re­ga­tion and Inte­gra­tion in a Mod­u­lar Network

    “Com­pu­ta­tional analy­sis of time-​​course data with an under­ly­ing causal struc­ture is needed in a vari­ety of domains, includ­ing neural spike trains, stock price move­ments, and gene expres­sion lev­els. How­ever, it can be chal­leng­ing to deter­mine from just the numer­i­cal time course data alone what is coor­di­nat­ing the vis­i­ble processes, to sep­a­rate the under­ly­ing prima facie causes into gen­uine and spu­ri­ous causes and to do so with a fea­si­ble com­pu­ta­tional com­plex­ity. For this pur­pose, we have been devel­op­ing a novel algo­rithm based on a frame­work that com­bines notions of causal­ity in phi­los­o­phy with algo­rith­mic approaches built on model check­ing and sta­tis­ti­cal tech­niques for mul­ti­ple hypothe­ses test­ing. The causal rela­tion­ships are described in terms of tem­po­ral logic for­mu­lae, refram­ing the infer­ence prob­lem in terms of model check­ing. The logic used, PCTL, allows descrip­tion of both the time between cause and effect and the prob­a­bil­ity of this rela­tion­ship being observed. We show that equipped with these causal for­mu­lae with their asso­ci­ated prob­a­bil­i­ties we may com­pute the aver­age impact a cause makes to its effect and then dis­cover sta­tis­ti­cally sig­nif­i­cant causes through the con­cepts of mul­ti­ple hypoth­e­sis test­ing (treat­ing each causal rela­tion­ship as a hypoth­e­sis), and false dis­cov­ery con­trol. By explor­ing a well-​​chosen fam­ily of poten­tially all sig­nif­i­cant hypothe­ses with rea­son­ably min­i­mal descrip­tion length, it is pos­si­ble to tame the algorithm’s com­pu­ta­tional com­plex­ity while explor­ing the nearly com­plete search-​​space of all prima facie causes. We have tested these ideas in a num­ber of domains and illus­trate them here with two examples.”

    time-​​series sta­tis­tics frame­work dynamical-​​systems to-​​read
  • [1206.5959] The Online Replace­ment Path Problem

    “We study a nat­ural online vari­ant of the replace­ment path prob­lem. The textit{replacement path prob­lem} asks to find for a given graph $G = (V,E)$, two des­ig­nated ver­tices $s,tin V$ and a short­est $s$-$t$ path $P$ in $G$, a textit{replacement path} $P_​e$ for every edge $e$ on the path $P$. The replace­ment path $P_​e$ is sim­ply a short­est $s$-$t$ path in the graph, which avoids the textit{failed} edge $e$. We adapt this prob­lem to deal with the nat­ural sce­nario, that the edge which failed is not known at the time of solu­tion imple­men­ta­tion. Instead, our prob­lem assumes that the iden­tity of the failed edge only becomes avail­able when the rout­ing mech­a­nism tries to cross the edge. This sit­u­a­tion is moti­vated by appli­ca­tions in dis­trib­uted net­works, where infor­ma­tion about recent changes in the net­work is only stored locally, and fault-​​tolerant opti­miza­tion, where an adver­sary tries to delay the dis­cov­ery of the mate­ri­al­ized sce­nario as much as pos­si­ble. Con­se­quently, we define the textit{online replace­ment path prob­lem}, which asks to find a nom­i­nal $s$-$t$ path $Q$ and detours $Q_​e$ for every edge on the path $Q$, such that the worst-​​case arrival time at the des­ti­na­tion is min­i­mized. Our main con­tri­bu­tion is a label set­ting algo­rithm, which solves the prob­lem in undi­rected graphs in time $O(m log n)$ and lin­ear space for all sources and a sin­gle des­ti­na­tion. We also present algo­rithms for exten­sions of the model to any bounded num­ber of failed edges.”

    operations-​​research plan­ning algo­rithms online-​​algorithms nudge-​​targets
  • [1206.6195] Par­rondo games with spa­tial depen­dence, II

    “…Again this sug­gests that the Par­rondo region (mu_​B is non­pos­i­tive and mu_[r,s] is pos­i­tive) has nonzero vol­ume in the limit. …”

    Parrondo-​​games game-​​theory counterintuitive-​​results sim­u­la­tion coop­er­a­tion
  • [1206.4648] Two-​​Manifold Prob­lems with Appli­ca­tions to Non­lin­ear Sys­tem Identification

    “Recently, there has been much inter­est in spec­tral approaches to learn­ing manifolds—so-called ker­nel eigen­map meth­ods. These meth­ods have had some suc­cesses, but their applic­a­bil­ity is lim­ited because they are not robust to noise. To address this lim­i­ta­tion, we look at two-​​manifold prob­lems, in which we simul­ta­ne­ously recon­struct two related man­i­folds, each rep­re­sent­ing a dif­fer­ent view of the same data. By solv­ing these inter­con­nected learn­ing prob­lems together, two-​​manifold algo­rithms are able to suc­ceed where a non-​​integrated approach would fail: each view allows us to sup­press noise in the other, reduc­ing bias. We pro­pose a class of algo­rithms for two-​​manifold prob­lems, based on spec­tral decom­po­si­tion of cross-​​covariance oper­a­tors in Hilbert space, and dis­cuss when two-​​manifold prob­lems are use­ful. Finally, we demon­strate that solv­ing a two-​​manifold prob­lem can aid in learn­ing a non­lin­ear dynam­i­cal sys­tem from lim­ited data.”

    sta­tis­tics inverse-​​problems system-​​identification algo­rithms nudge-​​targets bench­mark­ing
  • [1203.3367] Sto­chas­tic dif­fer­en­tial equa­tions for evo­lu­tion­ary dynam­ics with demo­graphic noise and mutations

    “We present a gen­eral frame­work to describe the evo­lu­tion­ary dynam­ics of an arbi­trary num­ber of types in finite pop­u­la­tions based on sto­chas­tic dif­fer­en­tial equa­tions (SDE). For large, but finite pop­u­la­tions this allows to include demo­graphic noise with­out requir­ing explicit sim­u­la­tions. Instead, the pop­u­la­tion size only rescales the ampli­tude of the noise. More­over, this frame­work admits the inclu­sion of muta­tions between dif­fer­ent types, pro­vided that muta­tion rates, $mu$, are not too small com­pared to the inverse pop­u­la­tion size 1/​N. This ensures that all types are almost always rep­re­sented in the pop­u­la­tion and that the occa­sional extinc­tion of one type does not result in an extended absence of that type. For $mu Nll1$ this lim­its the use of SDE’s, but in this case there are well estab­lished alter­na­tive approx­i­ma­tions based on time scale sep­a­ra­tion. We illus­trate our approach by a Rock-​​Scissors-​​Paper game with muta­tions, where we demon­strate excel­lent agree­ment with sim­u­la­tion based results for suf­fi­ciently large pop­u­la­tions. In the absence of muta­tions the excel­lent agree­ment extends to small pop­u­la­tion sizes.”

    finite-​​size-​​effects population-​​biology noise-​​in-​​design nudge-​​targets
  • [1206.5352] The Sub­word Com­plex­ity of k-​​Automatic Sequences is k-​​Synchronized

    “We show that the sub­word com­plex­ity func­tion p_​x (n), which counts the num­ber of dis­tinct fac­tors of length n of a k-​​automatic sequence x, is k-​​synchronized in the sense of Carpi. As an appli­ca­tion, we gen­er­al­ize recent results of Gold­stein. In con­trast, we show that func­tion which counts the num­ber of unbor­dered fac­tors of length n is not k-​​synchronized.”

    automata strings com­plex­ity nudge-​​targets
  • Con­vex hull algo­rithms — Wikipedia, the free encyclopedia

    “Com­put­ing the con­vex hull means that a non-​​ambiguous and effi­cient rep­re­sen­ta­tion of the required con­vex shape is con­structed. The com­plex­ity of the cor­re­spond­ing algo­rithms is usu­ally esti­mated in terms of n, the num­ber of input points, and h, the num­ber of points on the con­vex hull.”

    computational-​​geometry algo­rithms nudge-​​targets
  • [1205.6363] What Should Devel­op­ers Be Aware Of? An Empir­i­cal Study on the Direc­tives of API Documentation

    “Appli­ca­tion Pro­gram­ming Inter­faces (API) are exposed to devel­op­ers in order to reuse soft­ware libraries. API direc­tives are natural-​​language state­ments in API doc­u­men­ta­tion that make devel­op­ers aware of con­straints and guide­lines related to the usage of an API. This paper presents the design and the results of an empir­i­cal study on the direc­tives of API doc­u­men­ta­tion of object-​​oriented libraries. Its main con­tri­bu­tion is to pro­pose and exten­sively dis­cuss a tax­on­omy of 23 kinds of API directives.”

    digital-​​humanities doc­u­men­ta­tion text-​​mining software-​​development cultural-​​norms
  • Pub­li­ca­tions Avail­able Electronically

    God­fried T. Tou­s­saint, “The Erdos-​​Nagy the­o­rem and its ram­i­fi­ca­tions,” Proc. 11th Cana­dian Con­fer­ence on Com­pu­ta­tional Geom­e­try, Van­cou­ver, Canada, August 16–18 1999, pp. 9–12. Long ver­sion avail­able at: http://​www​.cs​.ubc​.ca/​c​o​n​f​e​r​e​n​c​e​s​/​C​CCG. Also: Tech­ni­cal Report No. SOCS-99.2, School of Com­puter Sci­ence, McGill Uni­ver­sity, June 18, 1999.

    nudge-​​targets geom­e­try genetic-​​programming-​​target low-​​hanging-​​fruit
  • Intro­duc­tion to Lam­ina Emer­gent Mech­a­nisms (LEMS) | Com­pli­ant Mechanisms

    “The fact that LEMs can be fab­ri­cated from pla­nar lay­ers influ­ences both what processes can be used for their man­u­fac­ture and what mate­ri­als may be used in their con­struc­tion. At the micro level, LEMS can be fab­ri­cated using single-​​layer MEMS fab­ri­ca­tion meth­ods and mate­ri­als, which offers sig­nif­i­cant cost and reli­a­bil­ity advan­tages. It also pro­vides oppor­tu­ni­ties for com­plex out-​​of-​​plane motion with only a sin­gle layer. At the macro level, man­u­fac­tur­ing processes used to make sta­tic struc­tures or com­po­nents for assem­bly can be used to cre­ate mech­a­nisms capa­ble of sophis­ti­cated motions and com­plex tasks. Example processes include stamp­ing, fine blank­ing, laser cut­ting, water jet cut­ting, plasma cut­ting, and wire elec­tri­cal dis­charge machin­ing (EDM). Some of these processes, such as stamp­ing, offer sig­nif­i­cant cost advan­tages for high-​​volume pro­duc­tion. Pla­nar fab­ri­ca­tion also allows the use of sheet goods to directly cre­ate mech­a­nisms. The use of low-​​cost, high-​​quality sheet goods has the poten­tial to dra­mat­i­cally reduce cost for high-​​volume pro­duc­tion. It also makes pos­si­ble the next char­ac­ter­is­tic: flat ini­tial state.”

    man­u­fac­tur­ing engineering-​​design fab­ri­ca­tion nudge-​​targets

Items of some interest:

These are my recent Pin​board​.in links:

  • [1006.5366] “Not only defended but also applied”: The per­ceived absur­dity of Bayesian inference

    “The mis­sion­ary zeal of many Bayesians of old has been matched, in the other direc­tion, by a view among some the­o­reti­cians that Bayesian meth­ods are absurd-​​not merely mis­guided but obvi­ously wrong in prin­ci­ple. We con­sider sev­eral exam­ples, begin­ning with Feller’s clas­sic text on prob­a­bil­ity the­ory and con­tin­u­ing with more recent cases such as the per­ceived Bayesian nature of the so-​​called dooms­day argu­ment. We ana­lyze in this note the intel­lec­tual back­ground behind var­i­ous mis­con­cep­tions about Bayesian sta­tis­tics, with­out aim­ing at a com­plete his­tor­i­cal cov­er­age of the rea­sons for this dismissal.”

    social-​​dynamics sta­tis­tics martial-​​arts-​​schools
  • [1206.3268] Fea­ture Selec­tion via Block-​​Regularized Regression

    “In this paper, we con­sid­ered the prob­lem of find­ing a sub­set of covari­ates in a high-​​dimensional space that affect the out­put vari­able when there is a block struc– ture in the covari­ates. In the con­text of asso­ci­a­tion map­ping, we pro­posed a regression-​​based model with a Markov chain prior that encodes the infor­ma­tion in the cor­re­la­tion struc­ture such as dis­tance and re– com­bi­na­tion rate between adja­cent SNP mark­ers. We demon­strated on the sim­u­lated and mouse data that our pro­posed algo­rithm can be used to iden­tify groups of SNP mark­ers as a rel­e­vant block of causal SNPs. The idea of rep­re­sent­ing the cor­re­la­tion struc­ture as a Markov chain in a vari­able selec­tion method to learn grouped rel­e­vant vari­ables can be gen­er­al­ized to use a graph­i­cal model as a prior in a vari­able selec­tion prob– lem to rep­re­sent an arbi­trary cor­re­la­tion struc­ture in vari­ables in a high-​​dimensional space. Another inter– est­ing exten­sion of the model is to model a struc­ture in out­put vari­ables as well when mea­sure­ments of mul– tiple out­put vari­ables are available.”

    sta­tis­tics bioin­for­mat­ics algo­rithms data-​​mining feature-​​extraction
  • Fil­ipe Kiss : A bet­ter git log

    “So, are you tired of this old and bored git log screen?”

    yes software-​​development git tricks-​​n-​​tips bash
  • Neu­roskep­tic: Brains are Dif­fer­ent on Macs

    “The paper goes into lots more detail, but the les­son for researchers is extremely sim­ple: don’t cross the streams of data-​​analysis. Set up your analy­sis stream and then use it on all of your data. Same hard­ware, same soft­ware, same set­tings. Imag­ine you’re doing a study com­par­ing brain struc­ture in two groups. Halfway through ana­lyz­ing your data, you upgrade your MacOS. All of the brains you ana­lyze after that will be, say, 5% “big­ger”. That’ll cer­tainly make your data much nois­ier, and if you hap­pen to ana­lyze most of Group A before Group B, it’ll give you a false pos­i­tive find­ing. Some­times you just can’t avoid changes in hard­ware or soft­ware — IT techs have a habit of upgrad­ing things with­out ask­ing — but in these cases, you should run the same data under the old and the new regime to see if it’s mak­ing a dif­fer­ence. Finally, it would be wrong to blame FreeSurfer for this. I’d be sur­prised if they were any worse than the other soft­ware pack­ages. Mix­ing and match­ing ver­sions is some­thing that the FreeSurfer devel­op­ers specif­i­cally warn against. This paper shows why.”

    data-​​analysis repro­ducibil­ity technical-​​assumptions anomalies-​​are-​​where-​​you-​​find-​​them
  • Plug: What is infer­en­tial­ism? « Odontomachus’s Blog

    “I’ve been crit­i­cal of objects and the idea of ref­er­ence for a while now. To me sen­tences and propo­si­tions, by virtue of their role as “moves” in social inter­ac­tions, are likely to have pri­or­ity in a prop­erly objec­tive account of mean­ing. Many puta­tive objects (e.g. cor­po­ra­tions or muta­ble dig­i­tal doc­u­ments) bor­der on being fic­tional, gain­ing their object­hood only through what we say about them; and many refer­ring phrases seem to refer to dif­fer­ent things, depend­ing on what is being pred­i­cated. I think this opin­ion would make me what Pere­grin calls a “strong infer­en­tial­ist”. Even­tu­ally I hope that think­ing clearly about seman­tics ought to (among other things) help bring calm to the cur­rent mass hys­te­ria which is the Seman­tic Web and Linked Data, and help steer all of that energy expen­di­ture to improve its consequence.”

    prag­ma­tism indirect-​​links phi­los­o­phy talking-​​about-​​thinking-​​and-​​the-​​reverse
  • [1206.3552] A Clas­si­fi­ca­tion for Com­mu­nity Dis­cov­ery Meth­ods in Com­plex Networks

    “In the last few years many real-​​world net­works have been found to show a so-​​called com­mu­nity struc­ture orga­ni­za­tion. Much effort has been devoted in the lit­er­a­ture to develop meth­ods and algo­rithms that can effi­ciently high­light this hid­den struc­ture of the net­work, tra­di­tion­ally by par­ti­tion­ing the graph. Since net­work rep­re­sen­ta­tion can be very com­plex and can con­tain dif­fer­ent vari­ants in the tra­di­tional graph model, each algo­rithm in the lit­er­a­ture focuses on some of these prop­er­ties and estab­lishes, explic­itly or implic­itly, its own def­i­n­i­tion of com­mu­nity. Accord­ing to this def­i­n­i­tion it then extracts the com­mu­ni­ties that are able to reflect only some of the fea­tures of real com­mu­ni­ties. The aim of this sur­vey is to pro­vide a man­ual for the com­mu­nity dis­cov­ery prob­lem. Given a meta def­i­n­i­tion of what a com­mu­nity in a social net­work is, our aim is to orga­nize the main cat­e­gories of com­mu­nity dis­cov­ery based on their own def­i­n­i­tion of com­mu­nity. Given a desired def­i­n­i­tion of com­mu­nity and the fea­tures of a prob­lem (size of net­work, direc­tion of edges, mul­ti­di­men­sion­al­ity, and so on) this review paper is designed to pro­vide a set of approaches that researchers could focus on.”

    via:cshalizi graph-​​theory com­mu­nity clas­si­fi­ca­tion algo­rithms nudge
  • [1205.0792] Exact Wavelets on the Ball

    “We develop an exact wavelet trans­form on the three-​​dimensional ball (i.e. on the solid sphere), which we name the fla­glet trans­form. For this pur­pose we first con­struct an exact har­monic trans­form on the radial line using damped Laguerre poly­no­mi­als and develop a cor­re­spond­ing quad­ra­ture rule. Com­bined with the spher­i­cal har­monic trans­form, this approach leads to a sam­pling the­o­rem on the ball and a novel three-​​dimensional decom­po­si­tion which we call the Fourier-​​Laguerre trans­form. We relate this new trans­form to the well-​​known Fourier-​​Bessel decom­po­si­tion and show that band-​​limitness in the Fourier-​​Laguerre basis is a suf­fi­cient con­di­tion to com­pute the Fourier-​​Bessel decom­po­si­tion exactly. We then con­struct the fla­glet trans­form on the ball through a har­monic tiling, which is exact thanks to the exact­ness of the Fourier-​​Laguerre trans­form (from which the name fla­glets is coined). The cor­re­spond­ing wavelet ker­nels have com­pact local­i­sa­tion prop­er­ties in real and har­monic space and their angu­lar aper­ture is invari­ant under radial trans­la­tion. We intro­duce a mul­tires­o­lu­tion algo­rithm to per­form the fla­glet trans­form rapidly, while cap­tur­ing all infor­ma­tion at each wavelet scale in the min­i­mal num­ber of sam­ples on the ball. Our imple­men­ta­tion of these new tools achieves float­ing point pre­ci­sion and is made pub­licly avail­able. We per­form numer­i­cal exper­i­ments demon­strat­ing the speed and accu­racy of these libraries and illus­trate their capa­bil­i­ties on a sim­ple denois­ing example.”

    wavelets geom­e­try representation-​​theory signal-​​processing answer-​​languages
  • [1205.3077] Efficiency-​​Revenue Trade-​​offs in Auctions

    “When agents with inde­pen­dent pri­ors bid for a sin­gle item, Myerson’s opti­mal auc­tion max­i­mizes expected rev­enue, whereas Vickrey’s second-​​price auc­tion opti­mizes social wel­fare. We address the nat­ural ques­tion of trade-​​offs between the two cri­te­ria, that is, auc­tions that opti­mize, say, rev­enue under the con­straint that the wel­fare is above a given level. If one allows for ran­dom­ized mech­a­nisms, it is easy to see that there are polynomial-​​time mech­a­nisms that achieve any point in the trade-​​off (the Pareto curve) between rev­enue and wel­fare. We inves­ti­gate whether one can achieve the same guar­an­tees using deter­min­is­tic mech­a­nisms. We pro­vide a neg­a­tive answer to this ques­tion by show­ing that this is a (weakly) NP-​​hard prob­lem. On the pos­i­tive side, we pro­vide polynomial-​​time deter­min­is­tic mech­a­nisms that approx­i­mate with arbi­trary pre­ci­sion any point of the trade-​​off between these two fun­da­men­tal objec­tives for the case of two bid­ders, even when the val­u­a­tions are cor­re­lated arbi­trar­ily. The major prob­lem left open by our work is whether there is such an algo­rithm for three or more bid­ders with inde­pen­dent val­u­a­tion distributions.”

    algo­rithms Pareto-​​front performance-​​measure multiobjective-​​optimization
  • Sym­bol­set

    “Sym­bol­sets are seman­tic sym­bol fonts. They work in mod­ern browsers and any­where Open­Type fea­tures are supported.”

    typog­ra­phy uni­code
  • [1204.6653] Elim­i­na­tion of Glass Arti­facts and Object Segmentation

    “Many images nowa­days are cap­tured from behind the glasses and may have cer­tain stains dis­crep­ancy because of glass and must be processed to make dif­fer­en­ti­a­tion between the glass and objects behind it. This research paper pro­poses an algo­rithm to remove the dam­aged or cor­rupted part of the image and make it con­sis­tent with other part of the image and to seg­ment objects behind the glass. The dam­aged part is removed using total vari­a­tion inpaint­ing method and seg­men­ta­tion is done using kmeans clus­ter­ing, anisotropic dif­fu­sion and water­shed trans­for­ma­tion. The final out­put is obtained by inter­po­la­tion. This algo­rithm can be use­ful to appli­ca­tions in which some part of the images are cor­rupted due to data trans­mis­sion or needs to seg­ment objects from an image for fur­ther processing.”

    image-​​segmentation image-​​processing nudge-​​targets algo­rithms
  • The whole of the law — Things from your life

    “But it’ll be your deci­sion, not iner­tia or fate. The ongo­ing cadence of ask­ing these ques­tions (and, maybe, the con­tent of any answers you come up with) will con­vene an open space for you to live in. A world where what­ever you do is right.”

    this
  • The Pirate Uni­ver­sity | Pirate university

    “The Pirate Uni­ver­sity is an on-​​line bul­letin board on which stu­dents post requests for aca­d­e­mic pub­li­ca­tions. You can com­pare it to an aca­d­e­mic wish list. Oth­ers, who know where to find these pub­li­ca­tions, reply and if pos­si­ble, pro­vide links to the resources searched. The Pirate Uni­ver­sity is not pro­vid­ing, stor­ing or shar­ing copy­righted mate­r­ial. An impor­tant ques­tion is if the upload­ing of arti­cles, pub­li­ca­tions is legal. If you are the copy­right holder of the arti­cle requested, there should be no prob­lem. Also in cer­tain cases, if you or your insti­tute have acquired the rights of the pub­li­ca­tion, or if it is free of rights, there shouldn’t be a prob­lem. It is prob­a­bly best to con­sult with your librar­ian to see which kind of pub­li­ca­tion is okay to share on the Internet.”

    academic-​​culture pub­lish­ing col­lab­o­ra­tion crowd­sourc­ing librar­i­ans open-​​access schol­ar­ship
  • [1206.3793] A dis­trib­uted classification/​estimation algo­rithm for sen­sor networks

    “…We pro­pose a novel coop­er­a­tive iter­a­tive algo­rithm which copes with the com­mu­ni­ca­tion con­straints imposed by the net­work and shows remark­able per­for­mance. Our main result is a rig­or­ous proof of the con­ver­gence of the algo­rithm and a char­ac­ter­i­za­tion of the limit behav­ior. We also show that, in the limit when the num­ber of sen­sors goes to infin­ity, the com­mon unknown para­me­ter is esti­mated with arbi­trary small error, while the clas­si­fi­ca­tion error con­verges to that of the opti­mal cen­tral­ized max­i­mum like­li­hood esti­ma­tor. We also show numer­i­cal results that val­i­date the the­o­ret­i­cal analy­sis and sup­port their pos­si­ble gen­er­al­iza­tion. We com­pare our strat­egy with the Expectation-​​Maximization algo­rithm and we dis­cuss trade-​​offs in terms of robust­ness, speed of con­ver­gence and imple­men­ta­tion simplicity.”

    distributed-​​processing collective-​​behavior sensor-​​networks algo­rithms nudge-​​targets
  • [1204.6391] Extend­ing par­tial rep­re­sen­ta­tions of func­tion graphs and per­mu­ta­tion graphs

    “Func­tion graphs are graphs rep­re­sentable by inter­sec­tions of con­tin­u­ous real-​​valued func­tions on the inter­val [0,1] and are known to be exactly the com­ple­ments of com­pa­ra­bil­ity graphs. As such they are rec­og­niz­able in poly­no­mial time. Func­tion graphs gen­er­al­ize per­mu­ta­tion graphs, which arise when all func­tions con­sid­ered are lin­ear. We focus on the prob­lem of extend­ing par­tial rep­re­sen­ta­tions, which gen­er­al­izes the recog­ni­tion prob­lem. We observe that for per­mu­ta­tion graphs an easy exten­sion of Golumbic’s com­pa­ra­bil­ity graph recog­ni­tion algo­rithm can be exploited. This approach fails for func­tion graphs. Nev­er­the­less, we present a polynomial-​​time algo­rithm for extend­ing a par­tial rep­re­sen­ta­tion of a graph by func­tions defined on the entire inter­val [0,1] pro­vided for some of the ver­tices. On the other hand, we show that if a par­tial rep­re­sen­ta­tion con­sists of func­tions defined on subin­ter­vals of [0,1], then the prob­lem of extend­ing this rep­re­sen­ta­tion to func­tions on the entire inter­val [0,1] becomes NP-​​complete.”

    graph-​​theory math-i-didn’t-know representation-​​theory ontol­ogy inter­est­ing
  • [1206.3294] Flex­i­ble Pri­ors for Exemplar-​​based Clustering

    “Exemplar-​​based clus­ter­ing meth­ods have been shown to pro­duce state-​​of-​​the-​​art results on a num­ber of syn­thetic and real-​​world clus­ter­ing prob­lems. They are appeal­ing because they offer com­pu­ta­tional ben­e­fits over latent-​​mean mod­els and can han­dle arbi­trary pair­wise sim­i­lar­ity mea­sures between data points. How­ever, when try­ing to recover under­ly­ing struc­ture in clus­ter­ing prob­lems, tai­lored sim­i­lar­ity mea­sures are often not enough; we also desire con­trol over the dis­tri­b­u­tion of clus­ter sizes. Pri­ors such as Dirich­let process pri­ors allow the num­ber of clus­ters to be unspec­i­fied while express­ing pri­ors over data par­ti­tions. To our knowl­edge, they have not been applied to exemplar-​​based mod­els. We show how to incor­po­rate pri­ors, includ­ing Dirich­let process pri­ors, into the recently intro­duced affin­ity prop­a­ga­tion algo­rithm. We develop an effi­cient max­prod­uct belief prop­a­ga­tion algo­rithm for our new model and demon­strate exper­i­men­tally how the expanded range of clus­ter­ing pri­ors allows us to bet­ter recover true clus­ter­ings in sit­u­a­tions where we have some infor­ma­tion about the gen­er­at­ing process.”

    clus­ter­ing algo­rithms
  • Mag­a­zine — The Case Against Cre­den­tial­ism — The Atlantic

    ’”ALL OF OUR WORK HAS GIVEN ME A VERY STRONG view,” Richard Boy­atzis told me one after­noon. The con­sult­ing firm Boy­atzis heads, McBer and Com­pany, was founded by David McClel­land in 1963. Its spe­cialty has been ana­lyz­ing what peo­ple actu­ally do in busi­ness jobs—not what their job descrip­tions say, but how they spend their time and which skills seem most impor­tant to their suc­cess. “I’ve come to see that when­ever a group insti­tutes a cre­den­tial­ing process, whether by licens­ing or insist­ing on advanced degrees, the espoused rhetoric is to enforce the stan­dards of pro­fes­sion­al­ism. This is true whether it’s among accoun­tants or plumbers or physi­cians. But the observed con­se­quences always seem to be these two: the exclu­sion of cer­tain groups, whether by inten­tion or not, and the estab­lish­ment of mediocre per­for­mance standards.“‘

    pro­fes­sion­al­iza­tion cre­den­tial­ing Andrew-​​Abbott-​​smiles-​​in-​​Chicago author­ity exper­tise cultural-​​assumptions disintermediation-​​targets
  • [1205.2483] Edge-​​clique graphs of cock­tail par­ties have unbounded rankwidth

    “In an attempt to find a polynomial-​​time algo­rithm for the edge-​​clique cover prob­lem on cographs we tried to prove that the edge-​​clique graphs of cographs have bounded rankwidth. How­ever, this is not the case. In this note we show that the edge-​​clique graphs of cock­tail party graphs have unbounded rank width.”

    open-​​questions nudge-​​targets graph-​​theory algo­rithms
  • [1206.3235] Iden­ti­fy­ing rea­son­ing pat­terns in games

    “We present an algo­rithm that iden­ti­fies the rea­son­ing pat­terns of agents in a game, by iter­a­tively exam­in­ing the graph struc­ture of its Multi-​​Agent Influ­ence Dia­gram (MAID) rep­re­sen­ta­tion. If the deci­sion of an agent par­tic­i­pates in no rea­son­ing pat­terns, then we can effec­tively ignore that deci­sion for the pur­pose of cal­cu­lat­ing a Nash equi­lib­rium for the game. In some cases, this can lead to expo­nen­tial time sav­ings in the process of equi­lib­rium cal­cu­la­tion. More­over, our algo­rithm can be used to enu­mer­ate the rea­son­ing pat­terns in a game, which can be use­ful for con­struct­ing more effec­tive com­put­er­ized agents inter­act­ing with humans.”

    game-​​theory infer­ence strat­egy nudge-​​targets learning-​​by-​​watching

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