Tag Archives: politics

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  • Pro­gres­sives and the Ron Paul fal­lac­ies — Salon​.com

    The fal­lacy in this rea­son­ing is glar­ing. The can­di­date sup­ported by pro­gres­sives — Pres­i­dent Obama — him­self holds heinous views on a slew of crit­i­cal issues and him­self has done heinous things with the power he has been vested. He has slaugh­tered civil­ians — Mus­lim chil­dren by the dozens — not once or twice, but con­tin­u­ously in numer­ous nations with drones, cluster bombs and other forms of attack. He has sought to over­turn a global ban on clus­ter bombs. He has insti­tu­tion­al­ized the power of Pres­i­dents — in secret and with no checks — to tar­get Amer­i­can cit­i­zens for assassination-​​by-​​CIA, far from any bat­tle­field. He has waged an unprece­dented war against whistle­blow­ers, the pro­tec­tion of which was once a lib­eral shib­bo­leth. He ren­dered per­ma­nently irrel­e­vant the War Pow­ers Res­o­lu­tion, a crown jewel in the list of post-​​Vietnam lib­eral accom­plish­ments, and thus enshrined the power of Pres­i­dents to wage war even in the face of a Con­gres­sional vote against it. His obses­sion with secrecy is so extreme that it has become darkly laugh­able in its man­i­fes­ta­tions, and he even worked to amend the Free­dom of Infor­ma­tion Act (another crown jewel of lib­eral leg­isla­tive suc­cesses) when com­pli­ance became inconvenient.

    pol­i­tics party-​​politics-​​in-​​particular cognitive-​​dissonance cultural-​​assumptions dialog-it-ain’t

  • A mod­est pro­posal to give Free Soft­ware equal legal stand­ing as pro­pri­etary. | Carlo Piana :: Law is Freedom ::

    Laws are more often than not an annoy­ance, despite their aim to improve the legal frame­work in any given field. Free Soft­ware (AKA “Open Source”) has thrieved despite the absence of any legal recog­ni­tion by the law, if not in spite of rules that clearly are shaped around pro­pri­etary soft­ware. In many juris­dic­tions it has passed the enforce­abil­ity test. So, no laws seem nec­es­sary to make it work. Yet, can some legal prin­ci­ple be put for­ward, and included in some laws, to help?

    via:Glyn-Moody licens­ing law con­tracts modest-​​proposals

  • 2011 in Review


    to-​​read to-​​keep-​​in-​​mind lists movies books comix

  • Best and Worst Sci­ence Fiction/​Fantasy Movies of 2011


    to-​​keep-​​in-​​mind movies lists

  • [1109.3248] Recon­struc­tion of sequen­tial data with den­sity models

    We intro­duce the prob­lem of recon­struct­ing a sequence of mul­ti­di­men­sional real vec­tors where some of the data are miss­ing. This prob­lem con­tains regres­sion and map­ping inver­sion as par­tic­u­lar cases where the pat­tern of miss­ing data is inde­pen­dent of the sequence index. The prob­lem is hard because it involves pos­si­bly mul­ti­val­ued map­pings at each vec­tor in the sequence, where the miss­ing vari­ables can take more than one value given the present vari­ables; and the set of miss­ing vari­ables can vary from one vec­tor to the next. To solve this prob­lem, we pro­pose an algo­rithm based on two redun­dancy assump­tions: vec­tor redun­dancy (the data live in a low-​​dimensional man­i­fold), so that the present vari­ables con­strain the miss­ing ones; and sequence redun­dancy (e.g. con­ti­nu­ity), so that con­sec­u­tive vec­tors con­strain each other. We cap­ture the low-​​dimensional nature of the data in a prob­a­bilis­tic way with a joint den­sity model, here the gen­er­a­tive topo­graphic map­ping, which results in a Gauss­ian mix­ture. Can­di­date recon­struc­tions at each vec­tor are obtained as all the modes of the con­di­tional dis­tri­b­u­tion of miss­ing vari­ables given present vari­ables. The recon­structed sequence is obtained by min­imis­ing a global con­straint, here the sequence length, by dynamic pro­gram­ming. We present exper­i­men­tal results for a toy prob­lem and for inverse kine­mat­ics of a robot arm.

    inverse-​​problems sta­tis­tics algo­rithms learning-​​from-​​data nudge-​​targets

  • [1110.5063] Recov­er­ing a Clipped Sig­nal in Sparseland

    In many data acqui­si­tion sys­tems it is com­mon to observe sig­nals whose ampli­tudes have been clipped. We present two new algo­rithms for recov­er­ing a clipped sig­nal by lever­ag­ing the model assump­tion that the under­ly­ing sig­nal is sparse in the fre­quency domain. Both algo­rithms employ ideas com­monly used in the field of Com­pres­sive Sens­ing; the first is a mod­i­fied ver­sion of Reweighted $ell_​1$ min­i­miza­tion, and the sec­ond is a mod­i­fi­ca­tion of a sim­ple greedy algo­rithm known as Triv­ial Pur­suit. An empir­i­cal inves­ti­ga­tion shows that both approaches can recover sig­nals with sig­nif­i­cant lev­els of clipping

    signal-​​processing infer­ence compressive-​​sensing algo­rithms nudge-​​targets

  • [1112.2316] Complexity-​​entropy causal­ity plane: a use­ful approach for dis­tin­guish­ing songs

    Nowa­days we are often faced with huge data­bases result­ing from the rapid growth of data stor­age tech­nolo­gies. This is par­tic­u­larly true when deal­ing with music data­bases. In this con­text, it is essen­tial to have tech­niques and tools able to dis­crim­i­nate prop­er­ties from these mas­sive sets. In this work, we report on a sta­tis­ti­cal analy­sis of more than ten thou­sand songs aim­ing to obtain a com­plex­ity hier­ar­chy. Our approach is based on the esti­ma­tion of the per­mu­ta­tion entropy com­bined with an inten­sive com­plex­ity mea­sure, build­ing up the complexity-​​entropy causal­ity plane. The results obtained indi­cate that this rep­re­sen­ta­tion space is very promis­ing to dis­crim­i­nate songs as well as to allow a rel­a­tive quan­ti­ta­tive com­par­i­son among songs. Addi­tion­ally, we believe that the here-​​reported method may be applied in prac­ti­cal sit­u­a­tions since it is sim­ple, robust and has a fast numer­i­cal implementation.

    signal-​​processing clas­si­fi­ca­tion data-​​analysis clus­ter­ing rep­re­sen­ta­tion music nudge-​​targets

  • [1112.6178] A gen­eral frame­work for online audio source separation

    We con­sider the prob­lem of online audio source sep­a­ra­tion. Exist­ing algo­rithms adopt either a slid­ing block approach or a sto­chas­tic gra­di­ent approach, which is faster but less accu­rate. Also, they rely either on spa­tial cues or on spec­tral cues and can­not sep­a­rate cer­tain mix­tures. In this paper, we design a gen­eral online audio source sep­a­ra­tion frame­work that com­bines both approaches and both types of cues. The model para­me­ters are esti­mated in the Max­i­mum Like­li­hood (ML) sense using a Gen­er­alised Expec­ta­tion Max­imi­sa­tion (GEM) algo­rithm with mul­ti­plica­tive updates. The sep­a­ra­tion per­for­mance is eval­u­ated as a func­tion of the block size and the step size and com­pared to that of an offline algorithm.

    signal-​​processing audio-​​segmentation sta­tis­tics algo­rithms meta­heuris­tics nudge-​​targets

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  • [1112.6209] Build­ing high-​​level fea­tures using large scale unsu­per­vised learning

    We con­sider the prob­lem of build­ing detec­tors for high-​​level con­cepts using only unsu­per­vised fea­ture learn­ing. For exam­ple, we would like to under­stand if it is pos­si­ble to learn a face detec­tor using only unla­beled images down­loaded from the inter­net. To answer this ques­tion, we trained a sim­ple fea­ture learn­ing algo­rithm on a large dataset of images (10 mil­lion images, each image is 200×200). The sim­u­la­tion is per­formed on a clus­ter of 1000 machines with fast net­work hard­ware for one week. Exten­sive exper­i­men­tal results reveal sur­pris­ing evi­dence that such high-​​level con­cepts can indeed be learned using only unla­beled data and a sim­ple learn­ing algorithm.

    image-​​analysis image-​​segmentation unsupervised-​​learning learning-​​by-​​doing feature-​​extraction nudge-​​targets

  • [1105.0158] Detect­ing emer­gent processes in cel­lu­lar automata with excess information

    Many nat­ural processes occur over char­ac­ter­is­tic spa­tial and tem­po­ral scales. This paper presents tools for (i) flex­i­bly and scal­ably coarse-​​graining cel­lu­lar automata and (ii) iden­ti­fy­ing which coarse-​​grainings express an automaton’s dynam­ics well, and which express its dynam­ics badly. We apply the tools to inves­ti­gate a range of exam­ples in Conway’s Game of Life and Hop­field net­works and demon­strate that they cap­ture some basic intu­itions about emer­gent processes. Finally, we for­mal­ize the notion that a process is emer­gent if it is bet­ter expressed at a coarser granularity.

    emer­gence com­plex­ol­ogy cellular-​​automata signal-​​processing nudge-​​targets

  • [1008.0901] Con­ver­gence to global con­sen­sus in opin­ion dynam­ics under a non­lin­ear voter model

    We pro­pose a non­lin­ear voter model to study the emer­gence of global con­sen­sus in opin­ion dynam­ics. In our model, agent $i$ agrees with one of binary opin­ions with the prob­a­bil­ity that is a power func­tion of the num­ber of agents hold­ing this opin­ion among agent $i$ and its near­est neigh­bors, where an adjustable para­me­ter $alpha$ con­trols the effect of herd behav­ior on con­sen­sus. We find that there exists an opti­mal value of $alpha$ lead­ing to the fastest con­sen­sus for lat­tices, ran­dom graphs, small-​​world net­works and scale-​​free net­works. Qual­i­ta­tive insights are obtained by exam­in­ing the spa­tiotem­po­ral evo­lu­tion of the opin­ion clusters.

    agent-​​based social-​​dynamics network-​​theory com­plex­ol­ogy nudge-​​targets

  • [1110.4876] REBOUND: An open-​​source multi-​​purpose N-​​body code for col­li­sional dynamics

    REBOUND is a new multi-​​purpose N-​​body code which is freely avail­able under an open-​​source license. It was designed for col­li­sional dynam­ics such as plan­e­tary rings but can also solve the clas­si­cal N-​​body prob­lem. It is highly mod­u­lar and can be cus­tomized eas­ily to work on a wide vari­ety of dif­fer­ent prob­lems in astro­physics and beyond.

    sim­u­la­tion computational-​​science astro­physics numerical-​​methods sim­u­la­tor library open-​​source nudge-​​targets

  • [1112.5908] Query Answer­ing under Match­ing Depen­den­cies for Data Clean­ing: Com­plex­ity and Algorithms

    Match­ing depen­den­cies (MDs) have been recently intro­duced as declar­a­tive rules for entity res­o­lu­tion (ER), i.e. for iden­ti­fy­ing and resolv­ing dupli­cates in rela­tional instance $D$. A set of MDs can be used as the basis for a pos­si­bly non-​​deterministic mech­a­nism that com­putes a duplicate-​​free instance from $D$. The pos­si­ble results of this process are the clean, “min­i­mally resolved instances” (MRIs). There might be sev­eral MRIs for $D$, and the “resolved answers” to a query are those that are shared by all the MRIs. We inves­ti­gate the prob­lem of com­put­ing resolved answers. We look at var­i­ous sets of MDs, devel­op­ing syn­tac­tic cri­te­ria for deter­min­ing (in)tractability of the resolved answer prob­lem, includ­ing a dichotomy result. For some tractable classes of MDs and con­junc­tive queries, we present a query rewrit­ing method­ol­ogy that can be used to retrieve the resolved answers. We also inves­ti­gate con­nec­tions with “con­sis­tent query answer­ing”, deriv­ing fur­ther tractabil­ity results for MD-​​based ER.

    data­bases graph-​​theory algo­rithms nudge-​​targets

  • The Wash­room Game by Jan Heufer :: SSRN

    This arti­cle analy­ses a game where play­ers sequen­tially choose either to become insid­ers and pick one of finitely many loca­tions or to remain out­siders. They will only become insid­ers if a min­i­mum dis­tance to the next player can be assured; their sec­ondary objec­tive is to max­i­mize the min­i­mal dis­tance to other play­ers. This is illus­trated by con­sid­er­ing the strate­gic behav­ior of men choos­ing from a set of uri­nals in a pub­lic lava­tory. How­ever, besides very sim­i­lar sit­u­a­tions (e.g. set­tling of res­i­dents in a newly devel­oped area, the selec­tion of food patches by for­ag­ing ani­mals, choos­ing seats in wait­ing rooms or lines in a swim­ming pool), the game might also rel­e­vant to the prob­lem of plac­ing bill­boards attempt­ing to catch the atten­tion of passers-​​by or sim­i­lar eco­nomic sit­u­a­tions. In the non-​​cooperative equi­lib­rium, all insid­ers behave as if they coop­er­ated with each other and min­i­mized the total num­ber of insid­ers. It is shown that strate­gic behav­ior leads to an equi­lib­rium with sub­stan­tial under uti­liza­tion of avail­able loca­tions. Increas­ing the num­ber of loca­tions tends to decrease uti­liza­tion. The removal of some loca­tions which leads to gaps can not only increase rel­a­tive uti­liza­tion but even absolute max­i­mum capacity.

    game-​​theory agent-​​based com­plex­ol­ogy eco­nom­ics nudge-​​targets

  • [1109.0777] Effi­cient and Cor­rect Sten­cil Com­pu­ta­tion via Pat­tern Match­ing and Sta­tic Typing

    Sten­cil com­pu­ta­tions, involv­ing oper­a­tions over the ele­ments of an array, are a com­mon pro­gram­ming pat­tern in sci­en­tific com­put­ing, games, and image pro­cess­ing. As a pro­gram­ming pat­tern, sten­cil com­pu­ta­tions are highly reg­u­lar and amenable to opti­mi­sa­tion and par­al­leli­sa­tion. How­ever, general-​​purpose lan­guages obscure this reg­u­lar pat­tern from the com­piler, and even the pro­gram­mer, pre­vent­ing opti­mi­sa­tion and obfus­cat­ing (in)correctness. This paper fur­thers our work on the Ypnos domain-​​specific lan­guage for sten­cil com­pu­ta­tions embed­ded in Haskell. Ypnos allows declar­a­tive, abstract spec­i­fi­ca­tion of sten­cil com­pu­ta­tions, expos­ing the struc­ture of a prob­lem to the com­piler and to the pro­gram­mer via spe­cialised syn­tax. In this paper we show the decid­able safety guar­an­tee that well-​​formed, well-​​typed Ypnos pro­grams can­not index out­side of array bound­aries. Thus index­ing in Ypnos is safe and run-​​time bounds check­ing can be elim­i­nated. Pro­gram infor­ma­tion is encoded as types, using the advanced type-​​system fea­tures of the Glas­gow Haskell Com­piler, with the safe-​​indexing invari­ant enforced at com­pile time via type checking.

    domain-​​specific-​​language algo­rithms grid-​​computing nudge-​​targets

  • What’s Chal­leng­ing About Paul? : Lawyers, Guns & Money

    It’s wrong to think of Ron Paul’s racism and his lib­er­tar­i­an­ism as two dis­tinct parts of his polit­i­cal per­sona, when in fact they are deeply tied together. White suprema­cists under­stand what Glenn, appar­ently, does not; the absence of Fed­eral author­ity makes it eas­ier for pri­vate actors and local gov­ern­ments to repress the civil and polit­i­cal rights of minori­ties. Paul’s lib­er­tar­i­an­ism emerged in a regional and cul­tural con­text that was deeply hos­tile to Fed­eral efforts at inte­gra­tion. The newslet­ters give strong indi­ca­tion that none of this is lost on Ron Paul. A notional Pres­i­dent Paul is just as likely to use the pow­ers of the office to gut Fed­eral enforce­ment of a wide range of civil lib­er­ties pro­tec­tions as he is to do any of the things that Glenn would like him to do.

    pol­i­tics lib­er­tar­i­an­ism racism con­ser­vatism pop­ulism

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  • The Econ­o­mist on the Repub­li­cans « The Reality-​​Based Community

    The Econ­o­mist – despite its unerr­ing judg­ment about  books on crime con­trol and drug pol­icy – can­not be justly described a Demo­c­ra­tic or lib­eral pub­li­ca­tion; it iden­ti­fies itself as “pro-​​business, right-​​of-​​centre.” But, unlike the friends of plu­toc­racy on this side of the Atlantic, the folks at The Econ­o­mist believe in prin­ci­ples other than dereg­u­la­tion of enter­prise and low taxes on the rich. More­over, they remain largely reality-​​based, eschew­ing wingnut postmodernism.

    con­ser­vatism pol­i­tics jour­nal­ism

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  • Deus Ex Mal­con­tent: Quote of the Day

    “Again, there’s a point to be made that it’s a waste of time and copy-​​space to give Paul’s ram­blings any more cre­dence than those of the recently released Belle­vue patient who’s now staked out a soap­box in the mid­dle of Cen­tral Park. For Christ’s sake, in 1977 Jimmy Carter implored this coun­try to make the tiny sac­ri­fice of drop­ping the ther­mo­stat a few degrees and wear­ing a sweater — and he was pub­licly cas­ti­gated for it. You think Amer­i­cans are gonna go for the aban­don­ment of entire swaths of the coun­try and its peo­ple every time a dis­as­ter like a mon­ster hur­ri­cane hits? You’re even more of a lunatic than Ron Paul — and that’s not easy.”

    lib­er­tar­i­an­ism pol­i­tics amusing-​​pseudorationalists-​​at-​​the-​​gate Thun­der­domes

  • The Exile Bib­lio­phile: Books: Own­ing them, Lov­ing them

    “So, I recently dis­cov­ered Stacked Up: Writ­ers Show off their Shelves, which is exactly what it sounds like. Short inter­views with writ­ers and some of their books. Just won­der­ful, though a bit too NYCen­tric to be truly invig­o­rat­ing. I just don’t get that worked up over THE BIG DEAL that is NYC. Give me space, keep your crowds! But, NYC is where a LOT of writ­ers live, so I can’t be too cranky about it. Hope­fully the Stacked Up folks will one day be able to get off the lit­tle island and out into the real world. Any­way, go enjoy these things Book Folk– you’re not alone.”

    books bib­lio­ma­nia book­shelves another-​​tag-​​involving-​​the-​​word-​​books author­ship writing-​​culture video

  • Cre­ative Com­mons Is Not Pub­lic Domain | Com­pound Eye, Sci­en­tific Amer­i­can Blog Network

    “Again, I do not know that the blog­gers didn’t write the pho­tog­ra­phers to obtain commercial-​​use per­mis­sion. But I doubt it. My judge­ment is borne from per­sonal expe­ri­ence. I see my images pop­ping up on com­mer­cial blogs all the time, and fewer than one in ten asks my per­mis­sion. I don’t mean to sin­gle out WIRED, either. I’m only pick­ing on them for the recent ant exam­ple. In real­ity, many com­mer­cial blog net­works show ram­pant dis­re­gard for the rights of artists, pho­tog­ra­phers, and musi­cians. They may not have been caught, yet, but they could incur sub­stan­tial legal lia­bil­ity when a copy­right owner decides to seek dam­ages. After all, using an image beyond the bounds of the license is break­ing the law. The bot­tom line is this: if some­one else’s cre­ative work is help­ing you make money, you have a moral and a legal oblig­a­tion to reach an agree­ment with that per­son about the terms of use. Cre­ative Com­mons is sup­posed to make this eas­ier, but it only works if the con­tent con­sumers treat CC as a con­tract and not a blan­ket license for free use. Cre­ative Com­mons is not pub­lic domain.”

    creative-​​commons intellectual-​​property copy­right cultural-​​assumptions