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  178. 10-601 Bias-Variance
  179. 10-601 Markov Decision Processes and Reinforcement Learning
  180. 10-601 Network Models
  181. 2008 Political Blogs
  182. 20 Newsgroups
  183. 28 subjects
  184. 4-square data and location-based Twitter data
  185. ACL Anthology
  186. ACL Antology
  187. A collection of categorized document
  188. A notion of word order
  189. A simple model of global cascades on random networks
  190. Aasish Project Abstract
  191. Aasish papers
  192. Adamic, Zhang, Bakshy, and Ackerman, Knowledge Sharing and Yahoo Answers: Everyone Knows Something, WWW 2008
  193. Agarwal, ICWSM 2009
  194. Agarwal et al ICWSM 2009
  195. Alice’s Adventures in Wonderland by Lewis Carroll
  196. An Experimental Study of the Coloring Problem on Human Subject Networks
  197. Apappu writeup of Roth talk
  198. Apappu writeup on Cohn and Blunsom
  199. Apappu writeup on Collins
  200. Apappu writeup on Lee Giles
  201. ArXiv Comprehensive
  202. Autolab Guide for TA
  203. Automatic Evaluation Method
  204. BA model
  205. Bbd and rbalasub - project status report
  206. Bbd project abstract
  207. Behavioral adaptation
  208. Bernoulli Naive Bayes
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  210. BibSonomy
  211. Bipartite graph
  212. Bipartite graphs
  213. Blair-Goldensohn et al, 2008
  214. Blog hyperlink cascades
  215. Bo Pang Sujith Ravi 2012 Revisiting the Predictability of Language: Response Completion in Social Media
  216. Borkar 2001 Automatic Segmentation of Text Into Structured Records
  217. Breck et al.2007
  218. British National Corpus
  219. Build an anxiety index for LiveJournal, an active blogging community
  220. Cascading Behavior in Blog Networks
  221. Cascading Behavior in Large Blog Graphs
  222. Category
  223. Celex corpus
  224. Centrality scores
  225. Choi et al 2005
  226. Choi et al 2006
  227. Choudhury et al ICWWW 2010
  228. Chun-Nam John Yu, Hofmann , Learning structural SVMs with latent variables 2009
  229. Class Meeting for 10-710 08-30-2011
  230. Class meeting for 10-605 2012 02 09
  231. Class meeting for 10-605 2012 02 14
  232. Class meeting for 10-605 Midterm review
  233. Class meeting for 10-605 Project Reports
  234. Clinical IE Project F10
  235. Clustering coefficient C
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  239. Cohen and Hersh Briefings in Bioinformatics 2005
  240. Community structure in social and biological networks
  241. Compare BinLu Rada Two Papers
  242. Compare Ku Akcora
  243. Compare Ramage Naaman
  244. Compare latentfriend familiarstranger
  245. Comparison Rosen-Zvi el al and cohn et al
  246. Comparison of Birke07 and Birke06
  247. Comparison of Topic Evolution Analysis with Citations
  248. Complement Naive Bayes
  249. Computational Approaches to Figurative Language
  250. Conditional random fields
  251. Conductance
  252. Conjugate Gradient Method
  253. Constraint Satisfaction
  254. Content-agnostic factors on video popularity
  255. Content recommendation
  256. Convex programming
  257. Cora
  258. Correlational Learning
  259. Cross-Lingual Mixture Model for Sentiment Classification, Xinfan Meng, Furu Wei, Xiaohua Liu, Ming Zhou, Ge Xu, Houfeng Wang, ACL 2012
  260. D. McAllester and J. Keshet NIPS 2010
  261. Das Sarma, Jain, and Yu, Dynamic Relationship and Event Discovery, WSDM 2011
  262. Dataset:ODP
  263. Dataset:Wordnet
  264. Decide the number of mixture components in grouped data
  265. Decision tree
  266. Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process
  267. Dependency Networks for Inference, Collaborative Filtering, and Data Visualization
  268. Detecting Topic Evolution in Scientific Literature: How Can Citations Help?
  269. Determining Social Network Attributes
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  271. Diffuses
  272. Diffusion models
  273. Document modeling
  274. Dogster
  275. Dong and Fu, Cultural difference in image tagging, SIGCHI, Atlanta, Georgia: ACM, 2010, pp. 981-984
  276. Dsafad
  277. Dwijaya Social Media Analysis
  278. E. Minkov et al.
  279. EachMovie
  280. Edinburgh Corpus
  281. Elegans scientific corpus
  282. Emotion Corpus (Upinion)
  283. EntropicGraphRegularization
  284. Entropy Minimization for Semi-supervised Learning
  285. Esuli and Sebastiani 2006
  286. Esuli et al. 2006
  287. EuTrans Corpus
  288. Eugene Charniak et al, ACL 2000
  289. Expectation-maximization algorithm
  290. Expert Search
  291. Expert search
  292. Explain the downward movement of stock prices using sentiment analysis methods
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  296. Facebook
  297. Farkas et al., 2010
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  299. Final-project-review
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  304. Forest Fire graph generation
  305. Fox et, ICML2008
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  309. GM1
  310. Gates 5222
  311. GaussianJointDistCommands.m
  312. Geotagged Tweets
  313. Gibbs Random Field
  314. Gilad Mishne and Maarten de Rijke, Capturing Global Mood Levels using Blog Posts, AAAI '06
  315. Gini coefficient
  316. Girju et al., 2006
  317. Graph Cut
  318. Graph Generation
  319. Graph coloring
  320. Graphical Games
  321. Graphical Models with Gibbs sampling and Expectation-Maximization methods
  322. Group-based classification model
  323. Guide for Happy Hadoop Hacking
  324. HITS
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  328. Hansards
  329. Harper et al., CHI 2009
  330. Hassan et al, ACL 2010
  331. Hearst, 1992
  332. Hearts, 1992
  333. Here
  334. Hidden Markov Model
  335. Hierarchical Dirichlet process
  336. Hill Climbing
  337. HotCopper
  338. How people evaluate information in a social Q&A environment
  339. How to use the video equipment
  340. Hu SIGKDD 2004
  341. Hu and Liu, 2004
  342. Identify the latent class as well as dyadic events
  343. Identifying high-quality content in social media sites
  344. Identity and Search in Social Networks
  345. Incorporate both methods
  346. Incremental Gibbs sampling
  347. Independent Learning
  348. Inductive content analysis
  349. Industry Sector
  350. Inference Cost
  351. Inferring networks of diffusion
  352. International events involving entities from 450 countries over the 2000-2005 time period
  353. Jason S Kessler icwsm09
  354. Jasonkjohnson noyear orbit product representation and correction of gaussian belief propagation
  355. Jensen-Shannon divergence
  356. JointDistCommands.m
  357. Joyce & Kraut, JCMC 2006
  358. K-anonymity
  359. K-exposed
  360. K-means
  361. KL Divergence
  362. KNN
  363. Kamps LREC 2004
  364. KeisukeKamataki project abstract
  365. Kessler et al. 2009
  366. Klein Royal-Society1952
  367. Krogh 1994
  368. L. Ku, Y. Liang, and H. Chen. Opinion extraction, summarization and tracking in news and blog corpora. In Proceedings of AAAI-2006
  369. LDA
  370. LIBSVM -- A Library for Support Vector Machines
  371. Lack of Sparsity
  372. Lampe & Johnston, SIGGROUP 2005
  373. Learning Influence Probabilities as
  374. Learning Multilingual Subjective Language via Cross-Lingual Projections
  375. Legal* Free Hungry Shark Evolution Cheats Hack Coins Gems Mod Generator No Human Verification 2023
  376. Leskovec, ACM Conference on Electronic Commerce (EC), 2006.
  377. Liang and Klein 2009 Online EM for Unsupervised Models
  378. Liben-Nowell PNAS 2005
  379. Lin, 1999
  380. Lin et al KDD 2011
  381. Lindsay 2008
  382. Linear Threshold Models - Diffusion models
  383. List of First-Draft Project Proposals for 10-802 in Spring 2011
  384. List of Second-Draft Project Proposals for 10-802 in Spring 2011
  385. Liu K and Tang L. CIKM'11
  386. Liu and Nocedal, 1989
  387. Liuliu project abstract
  388. Liuy project abstract
  389. LiveJournal post stream gathered using atom listener
  390. Logistic Regression
  391. Luke et al, Uncertainty in Artificial Intelligence 2005
  392. M. Kim and J. Leskovec. ICML'12
  393. MCMC algorithm for posterior inference under hierarchical Dirichlet process mixtures
  394. Macskassy: Contextual linking behavior of bloggers
  395. Mao and G. Lebanon, 2006
  396. Marcken, 1996
  397. Mark my words!
  398. Martins et al. EMNLP 2011. Structured Sparsity in Structured Prediction
  399. Max-Margin Markov Networks
  400. Maxima
  401. Maximization of the benefit function known as "modularity"
  402. Maximum Entropy Markov Models
  403. Mehdi project abstract
  404. MemeTracker
  405. Midterm 805 project report
  406. Miray Dongyang Niting project proposal
  407. Mnduong project abstract
  408. Model Dataset
  409. Models of metaphor in NLP
  410. Mrinmaya et. al. WWW'12
  411. Msharifi Han wirteup of Borthwick, Sterling, Agichtein and Grishman
  412. Multi-class Classification
  413. Multi-linear regression
  414. Munteanu and Marcu, 2006
  415. My Singing Monsters Hack Cheats Generator Tool on iOS and Android 2023
  416. NETtalk corpus
  417. NIPS 1988-1999
  418. NTCIR
  419. Nallapati Cohen Link PLSA LDA
  420. Named Entity Recognition with Character-Level Models
  421. Naïve Bayes
  422. Nematode biology abstracts
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  429. NiLao LiuLiu YandongLiu project abstract
  430. Nlao Project Abstract
  431. Normalized Learning
  432. Normalized discounted cumulative gain
  433. NqiPresentation.pptx
  434. Nschneid Liuy Project status update
  435. OOV Detection from ASR Hypothesis - Project Midway Report
  436. OOV dection from ASR hypothesis - Project Midway Report
  437. Observe and track the popular events or topics
  438. Old midterm links
  439. Online inference model for LDA
  440. Overfitting
  441. Overlapping communities
  442. Overparametrization
  443. PNAS Dataset
  444. PRISMA
  445. Pang and Lee, 2004
  446. Paper:Klein et al, CoNLL 2003
  447. Paper:Phrase Clustering for Discriminative Learning
  448. PennBioIE
  449. Perplexity
  450. Philgoo Han writeup of Giles Talk
  451. Philipp Keller
  452. Philipp Keller's dataset
  453. Phrase Clustering for Discriminative Learning
  454. Pitt/OpinionFinder subjectivity lexicon
  455. Predict the attributes and links in Temporal Social Network.
  456. Presentation
  457. Principal Component Analysis
  458. Privacy attacks
  459. Project Mehdi Samadi
  460. Project Second Draft-Subhodeep Manaj
  461. Project presentation
  462. Projects for Machine Learning with Large Datasets 10-605 in Spring 2012
  463. Projects for Machine Learning with Large Datasets 10-605 in Spring 2014
  464. Proposal Draft
  465. Proposal Draft Yanbo Ming
  466. Proposed a discrete temporal model family that is capable of modeling network evolution, while maintaining the flexibility of ERGMs. It also proposed such models to build upon ERGMs as much as possible.
  467. PubMed
  468. Qhe et al Detecting Topic Evo 2009
  469. Question-Answer Sharing Analysis
  470. Question types
  471. Ramnath Balasubramanyan et. al. ICWSM 2012
  472. Random graphs
  473. Rbalasub writeup of talk by Dan Roth at U Pitt on Oct 2nd, 2009
  474. Rbosaghz project progress
  475. Read the Web Data
  476. Reality Mining
  477. Relational Markov network
  478. Result
  479. Result of AD using small-world
  480. Reuters-21578
  481. Review for Exploiting Relational Structure to Understand Publication Patterns in High-Energy Physics
  482. Road Game
  483. Roja Bandari et. al. ICWSM 2012
  484. Roll.m
  485. Rosenfield and Huang, 1992
  486. Roth, D. et al, ICML 2005
  487. SVM
  488. Sahebi project proposal
  489. Sample project write-ups for 10-605
  490. Sampling
  491. Sarawagi and Cohen, 2004
  492. Scale-free networks
  493. Segmented Topic Model
  494. Selen project abstract
  495. Selen writeup of Bunescu 2006
  496. Sentence Level Sentiment Dataset
  497. Sequential influence modeling
  498. Several methods are used in this paper
  499. Sgopal1 Project Abstract
  500. Sgopal1 writeup on citeseer talk

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