Items of some interest:

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

Items of some interest…

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

  • 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

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

  • 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

Items of some interest…

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

  • Sell­ing the Idea of a Chris­t­ian Nation: David Barton’s Alter­nate Intel­lec­tual Uni­verse | Pol­i­tics | Reli­gion Dispatches

    “I use the term “debate” in quotes because it is fraud­u­lent. Even advo­cates of the view­point of the “god­less Con­sti­tu­tion” (such as his­to­ri­ans Isaac Kram­nick and R. Lau­rence Moore) fully under­stand the reli­gious base of Amer­i­can his­tory. They sug­gest sim­ply (as Jon Stew­art was try­ing to get at) that the framers rather delib­er­ately excluded reli­gion, not because they sought an exclu­sion of reli­gion from the pub­lic square, but sim­ply to avoid any spe­cial priv­i­leges for it at the fed­eral level. Even­tu­ally, those views were incor­po­rated into state laws through the 14th Amend­ment, through the plu­ral­iza­tion of Amer­i­can life in the twen­ti­eth cen­tury, and through the epochal court cases of the 1940s through the 1970s. The Chris­t­ian Nation “debate” is not really an intel­lec­tual con­test between legit­i­mate con­tend­ing view­points. Instead, it is a man­u­fac­tured “con­tro­versy” akin to the global warm­ing “debate.” On one side are pur­vey­ors of a rich and com­plex view of the past, includ­ing most his­to­ri­ans who have writ­ten and debated fiercely about the found­ing era. The “other side” is a group of ide­o­log­i­cal entre­pre­neurs who have cre­ated an alter­nate intel­lec­tual uni­verse based on a his­tor­i­cal fun­da­men­tal­ism. In their drive to cre­ate a usable past, they show lit­tle respect for the past as a for­eign country. ”

    Chris­tian­ity con­ser­vatism history-​​is-​​a-​​feature-​​not-​​a-​​bug sto­ry­telling
  • Poor Mojo’s Newswire: Twit­pic qui­etly changes Terms of Ser­vice, they can now sell any pic you upload

    “You retain all own­er­ship rights to Con­tent uploaded to Twit­pic. How­ever, by sub­mit­ting Con­tent to Twit­pic, you hereby grant Twit­pic a world­wide, non-​​exclusive, royalty-​​free, sub­li­censeable and trans­fer­able license to use, repro­duce, dis­trib­ute, pre­pare deriv­a­tive works of, dis­play, and per­form the Con­tent in con­nec­tion with the Ser­vice and Twitpic’s (and its suc­ces­sors’ and affil­i­ates’) busi­ness, includ­ing with­out lim­i­ta­tion for pro­mot­ing and redis­trib­ut­ing part or all of the Ser­vice (and deriv­a­tive works thereof) in any media for­mats and through any media channels.”

    Twit­ter intellectual-​​property EULA licens­ing
  • Trade Secrets and Pub­lished Patent Appli­ca­tions — Patent Law Blog (Patently-​​O)

    “Patent Pub­li­ca­tion Elim­i­nates Trade Secret: In a straight­for­ward opin­ion, the appel­late panel held once pub­lished, the infor­ma­tion in a patent appli­ca­tion should be con­sid­ered “gen­er­ally known and read­ily avail­able” and there­fore are no longer amenable to trade secret protection.  ”

    patents intellectual-​​property lawyers nondis­clo­sure