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- Class Meeting for 10-802 11/27/2012
- Class Meeting for 10-802 11/29/2012
- Class Meeting for 10-802 11/6/2012
- Class Meeting for 10-802 11/8/2012
- Class Presentation of J. Leskovec "Cost Effective Outbreak Detection in Networks"
- Class meeting for 10-405 Computing with GPUs
- Class meeting for 10-405 Deep Learning
- Class meeting for 10-405 Graph Architectures for ML
- Class meeting for 10-405 Guest lecture - tentative
- Class meeting for 10-405 Hadoop Overview
- Class meeting for 10-405 LDA
- Class meeting for 10-405 Midterm review and catchup
- Class meeting for 10-405 Overview
- Class meeting for 10-405 Parallel Perceptrons
- Class meeting for 10-405 Parameter Servers
- Class meeting for 10-405 Probability Review
- Class meeting for 10-405 Randomized Algorithms
- Class meeting for 10-405 Review session for final
- Class meeting for 10-405 SGD and Hash Kernels
- Class meeting for 10-405 SGD for MF
- Class meeting for 10-405 SSL on Graphs
- Class meeting for 10-405 Streaming Naive Bayes
- Class meeting for 10-405 Unsupervised Learning On Graphs
- Class meeting for 10-405 Workflows For Hadoop
- Class meeting for 10-605 2012 01 17
- Class meeting for 10-605 2012 01 19
- Class meeting for 10-605 2012 01 24
- Class meeting for 10-605 2012 01 26
- Class meeting for 10-605 2012 01 31
- Class meeting for 10-605 2012 02 02
- Class meeting for 10-605 2012 02 07
- Class meeting for 10-605 2012 02 09
- Class meeting for 10-605 2012 02 14
- Class meeting for 10-605 2012 02 16
- Class meeting for 10-605 2012 02 18
- Class meeting for 10-605 2012 02 21
- Class meeting for 10-605 2012 02 28
- Class meeting for 10-605 2012 03 06
- Class meeting for 10-605 2012 03 20
- Class meeting for 10-605 2012 03 22
- Class meeting for 10-605 2012 03 27
- Class meeting for 10-605 2012 03 29
- Class meeting for 10-605 2012 04 03
- Class meeting for 10-605 2012 04 10
- Class meeting for 10-605 2012 04 12
- Class meeting for 10-605 2012 04 14
- Class meeting for 10-605 2012 04 16
- Class meeting for 10-605 2012 04 17
- Class meeting for 10-605 2013 01 14
- Class meeting for 10-605 2013 01 16
- Class meeting for 10-605 2013 01 21
- Class meeting for 10-605 2013 01 23
- Class meeting for 10-605 2013 01 28
- Class meeting for 10-605 2013 01 30
- Class meeting for 10-605 2013 02 04
- Class meeting for 10-605 2013 02 06
- Class meeting for 10-605 2013 02 11
- Class meeting for 10-605 2013 02 13
- Class meeting for 10-605 2013 02 18
- Class meeting for 10-605 2013 02 20
- Class meeting for 10-605 2013 02 25
- Class meeting for 10-605 2013 02 27
- Class meeting for 10-605 2013 03 04
- Class meeting for 10-605 2013 03 18
- Class meeting for 10-605 2013 03 20
- Class meeting for 10-605 2013 03 25
- Class meeting for 10-605 2013 03 27
- Class meeting for 10-605 2013 04 01
- Class meeting for 10-605 2013 04 03
- Class meeting for 10-605 2013 04 08
- Class meeting for 10-605 2013 04 10
- Class meeting for 10-605 2013 04 15
- Class meeting for 10-605 2013 04 17
- Class meeting for 10-605 2013 LDA 2
- Class meeting for 10-605 Advanced topics for SGD
- Class meeting for 10-605 Computing with GPUs
- Class meeting for 10-605 Deep Learning
- Class meeting for 10-605 First-Order Logics
- Class meeting for 10-605 GraphLab
- Class meeting for 10-605 Graph Architectures for ML
- Class meeting for 10-605 Graphs 2
- Class meeting for 10-605 Hadoop Overview
- Class meeting for 10-605 LDA
- Class meeting for 10-605 LDA 2
- Class meeting for 10-605 Midterm review
- Class meeting for 10-605 Midterm review and catchup
- Class meeting for 10-605 Overview
- Class meeting for 10-605 Parallel Perceptrons
- Class meeting for 10-605 Parallel Perceptrons 1
- Class meeting for 10-605 Parallel Perceptrons 2
- Class meeting for 10-605 Parallel Similarity Joins
- Class meeting for 10-605 Parameter Servers
- Class meeting for 10-605 Phrase Finding
- Class meeting for 10-605 Phrases with Stream and Sort
- Class meeting for 10-605 Probability Review
- Class meeting for 10-605 Project Reports
- Class meeting for 10-605 Randomized
- Class meeting for 10-605 Randomized Algorithms
- Class meeting for 10-605 Randomized Algorithms 2
- Class meeting for 10-605 Review session for final
- Class meeting for 10-605 Rocchio and Hadoop Workflows
- Class meeting for 10-605 SGD and Hash Kernels
- Class meeting for 10-605 SGD for MF
- Class meeting for 10-605 SGD for MF 2 and Randomized Algorithms
- Class meeting for 10-605 SSL on Graphs
- Class meeting for 10-605 Scalable FOL
- Class meeting for 10-605 Scalable PageRank
- Class meeting for 10-605 Scalable Testing
- Class meeting for 10-605 Similarity Joins
- Class meeting for 10-605 Spectral Clustering
- Class meeting for 10-605 Streaming Naive Bayes
- Class meeting for 10-605 Subsampling Graphs
- Class meeting for 10-605 Subsampling a Graph
- Class meeting for 10-605 Unsupervised Learning On Graphs
- Class meeting for 10-605 Workflows For Hadoop
- Class meeting for 10-605 Workflows For Hadoop 2
- Class meeting for 10-605 in Fall 2016 Hadoop Overview
- Class meeting for 10-605 in Fall 2016 Overview
- Class meeting for 10-605 in Fall 2016 Probability Review
- Class meeting for 10-605 in Fall 2016 Streaming Naive Bayes
- Click Dataset Google Yahoo
- Clinical IE Project F10
- Clone sets of Youtube videos
- Clustering
- Clustering coefficient C
- Cnet product reviews dataset
- Co-clustering documents and words using bipartite spectral graph partitioning
- Co-occurrence agreement probability
- Co-occurrence metrics
- Co-training
- CoNLL'00
- CoNLL'03
- CoNLL-X
- Codes (Faster kids) Clash of Clans Gems Generator New Updated Edition 2023 No Survey!
- Codes (Faster kids) V Bucks Generator New Updated Edition 2023 No Survey!
- Codes Free Pokemon Go Pokecoins Generator 2023 No Human Veryfication!!!
- Cohen 2000 hardening soft information sources
- Cohen 2000 whirl a word based information representation language
- Cohen 2003 a comparison of string distance metrics for name matching tasks
- Cohen 2005 stacked sequential learning
- Cohen and Carvalho, 2005
- Cohen and Hersh Briefings in Bioinformatics 2005
- Cohen et al IJCAI 2005
- Cohn 2005 semantic role labelling with tree conditional random fields
- Cohn et al, Advances in Neural Information Processing Systems 2001
- Collier et al., 2000
- Collier et al. Journal of Biomedical Semantics 2011
- CollocationDetection
- Common neighbors
- Community Detection
- Community structure
- Community structure in social and biological networks
- Comparative Study : Sentiment Analysis using Automated pattern based appraoch VS Single structured model
- Comparative Study of CQA : Anderson et al and Liu et al
- Comparative Study of Discriminative Models in SMT
- Compare BinLu Rada Two Papers
- Compare Esuli and Sebastiani LREC 2006 vs. Esuli and Sebastiani EACL 2006
- Compare Hassan et al, ICWSM 2009 and Document representation and query expansion models for blog recommendation
- Compare Ku Akcora
- Compare Leskovec et al. WWW 10 and Leskovec et al. WWW 08
- Compare Link Propagation Papers
- Compare Measuring User Influence in Twitter and Influentials, Networks, and Public Opinion Formation
- Compare Modeling Contagion Through Facebook News Feed and Cascading Behavior in Large Blog Graphs
- Compare Ramage Naaman
- Compare Rodriguez Barabasi
- Compare Y. Borghol et al. 2011 and The Untold Story of the Clones: Content-agnostic Factors that Impact YouTube Video Popularity
- Compare Yang et al Modeling Information Diffusion in Implicit Networks and Inferring the Diffusion and Evolution of Topics in Social Communities
- Compare Yano et al NAACL 2009 Link PLSA LDA
- Compare latentfriend familiarstranger
- Comparing Unsupervised Learning of Narrative Event Chains and Mining the web for fine-grained semantic verb relations
- Comparison: A Latent Variable Model for Geographic Lexical Variation and A probabilistic approach to spatiotemporal theme pattern mining on weblogs
- Comparison: Collier et al. Journal of Biomedical Semantics 2011 and Sadilek et al Sixth AAAI International Conference on Weblogs and Social Media (ICWSM)
- Comparison: O'Connor et al. ICWSM 2010 & Widespread Worry and Stock Market
- Comparison: Widespread Worry and the Stock Market versus Sentiment Detection Engine for Internet Stock Message Boards
- Comparison Andreevskaia et al ICWSM 2007 and MHurst KNigam RetrievingTopicalSentimentsFromOnlineDocumentColeections
- Comparison Das et al WSDM 2011 and Zhao et al AAAI 2007
- Comparison Mrinmaya et. al. WWW2012 and McCallum et al 2004
- Comparison Rosen-Zvi el al and cohn et al
- Comparison mixed membership topic poisson
- Comparison of Birke07 and Birke06
- Comparison of Topic Evolution Analysis with Citations
- Complement Naive Bayes
- Computational Approaches to Figurative Language
- Computational methods frequently used in Analysis of Social Media
- ConVote dataset
- Conditional Random Fields
- Conditional random fields
- Conductance
- Conference-Author dataset
- Conjugate Gradient Method
- Connections between the Lines: Augmenting Social Networks with Text
- Constraint Satisfaction
- Content-agnostic factors on video popularity
- Content recommendation
- Contrastive Estimation
- Controversial events detection
- Convex programming
- Cora
- Cora network
- Coreference Resolution in a Modular, Entity-Centered Model
- Corporate Elite Networks and Governance Changes in the 1980s
- Correlation coefficients
- Correlational Learning
- CosineSimilarity
- Cosine similarity
- Cosley, D., D. Huttenlocher, J. Kleinberg, X. Lan, and S. Suri. 2010. Sequential Influence Models in Social Networks.
- Cosley et al 2010
- Cost Effective Outbreak Detection in Networks
- Crescenzi et al, 2001
- Cross-Lingual Mixture Model for Sentiment Classification, Xinfan Meng, Furu Wei, Xiaohua Liu, Ming Zhou, Ge Xu, Houfeng Wang, ACL 2012
- Cross Document Coreference (CDC)
- Cucerzan and Yarowsky, SIGDAT 1999
- Cyberjournalist.net dataset
- D. Lange et al., CIKM 2010
- D. McAllester and J. Keshet NIPS 2010
- DBpedia
- Daly et al Social Lense: Personalization Around User Defined Collections for Filtering Enterprise Message Streams ICWSM 2011
- Dan Cosley, AAAI, 2010
- Dan and Yih, ICML 2005. Integer Linear Programming Inference for Conditional Random Fields
- Danescu-Niculescu-Mizil et. al., WWW 2009
- Das Sarma, Jain, and Yu, Dynamic Relationship and Event Discovery, WSDM 2011
- Das Sarma et. al., Dynamic Relationship and Event Discovery, WSDM 2011
- Dataset
- Dataset:MPQA
- Dataset:ODP
- Dataset:Wordnet
- Datasets studied in Analysis of Social Media
- Daume ICML 2009
- Daume and Marcu 2005 Learning as Search Optimization: Approximate Large Margin Methods for Structured Prediction
- Daume et al, 2006
- Daume et al, ML 2009
- Dave et. al., WWW 2003
- David M. Blei and Pedro J. Moreno, Topic Segmentation with an Aspect Hidden Markov Model, SIGIR 2001
- Davidov et al COLING 10
- DeNero et al, EMNLP 2008
- Decide the number of mixture components in grouped data
- Decision tree
- Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process
- Degan 1999 Similarity-based models of word cooccurrence probabilities
- Del.icio.us
- Delicious
- Denecke and Bernauer AIME 2007
- Denecke and Bernauer ARTIFICIAL INTELLIGENCE IN MEDICINE 2007
- Denis and Muller, Predicting Globally-Coherent Temporal Structures from Texts via Endpoint Inference and Graph Decomposition, IJCAI 2011
- Dependency Networks for Inference, Collaborative Filtering, and Data Visualization
- Dependency Parsing
- Dependency network
- Detecting Topic Evolution in Scientific Literature: How Can Citations Help?
- Detection of Ad Hominem attacks in blog and review data
- Determining Social Network Attributes
- Determining term subjectivity and term orientation for opinion mining.
- Diamonds Coins For Free – Newest My Singing Monsters Diamonds Coins Generator 2023! Free Diamonds Coins!!
- Dietterich 2008 gradient tree boosting for training conditional random fields
- Diffuses
- Diffusion
- Diffusion models
- Dirichlet distribution
- Distributional Similarity
- DmitryDavidov et al. CoNLL
- Do metaphors shape a listener's thinking?
- Document modeling
- Document representation
- Document representation and query expansion models for blog recommendation
- Dogster
- Domain-Assisted Product Aspect Hierarchy Generation: Towards Hierarchical Organization of Unstructured Consumer Reviews
- Dong and Fu, Cultural difference in image tagging, SIGCHI, Atlanta, Georgia: ACM, 2010, pp. 981-984
- Dong et al WWW 2010
- Draft schedule for 10-601B in Spring 2016
- Dreyer and Eisner, EMNLP 2006
- Dsafad
- Duplicate Document Detection
- Dwijaya Social Media Analysis
- Dyer et al, ACL 2011
- Dynamic Social Network Analysis using Latent Space Models
- E.A. Leicht, Structure of Time Evo citation networks 2007
- E. Minkov et al.
- E. Minkov et al. HLT/EMNLP 2005
- EHow.com
- EUROPARL
- EachMovie
- Edge betweenness
- Edinburgh Corpus
- Eisenstein et al 2011: Sparse Additive Generative Models of Text
- Eisenstein et al ACL 2011. Discovering Sociolinguistic Associations with Structured Sparsity
- Eisner algorithm
- Elegans scientific corpus
- Elworthy, 1994 Does Baum-Welch re-estimation help taggers
- Email network
- Emergence of scaling in random networks
- Emotion Corpus (Upinion)
- Empirical Risk Minimization
- Enron email corpus
- EntropicGraphRegularization
- EntropicGraphRegularizationSSC
- Entropy Gradient for Semi-Supervised Conditional Random Fields
- Entropy Minimization for Semi-supervised Learning
- Epinions
- Error correcting output coding
- Esuli and Sebastiani 2006
- Esuli and Sebastiani ACT2007
- Esuli and Sebastiani LREC 2006
- Esuli et al. 2006
- Etzioni 2004 methods for domain independent information extraction from the web an experimental comparison
- Etzioni 2005 unsupervised named entity extraction
- Etzioni 2005 unsupervised named entity extraction from the web an experimental study
- Etzioni et al., 2005
- EuTrans
- EuTrans Corpus
- Eugene Charniak et al, ACL 2000
- Event detection
- Expectation-maximization algorithm
- Expectation Maximization
- Expectation Regularization
- Expectation–maximization algorithm
- Expert Search
- Expert search
- Explain the downward movement of stock prices using sentiment analysis methods
- Exploiting Diverse Knowledge Sources via Maximum Entropy in NER
- Exploiting diverse knowledge sources via maximum entropy in named entity recognition, by A. Borthwick, J. Sterling, E. Agichtein, R. Grishman. In Proceedings of the sixth workshop on very large corpora, 1998.
- Extracting Opinion Expressions with semi-Markov Conditional Random Fields
- FBIS corpus
- FREE Ebay Generator PRO APK (Android Ios App)
- FREE METHOD* Nintendo Gift Card Codes Generator (2023) No Human Verification No Survey
- FREE Twitch Generator PRO APK (Android Ios App)
- Facebook dataset
- Fader et al EMNLP 2011
- Faloutsos KDD 2005
- Farkas et al., 2010
- Fast and scalable algorithms for semi-supervised link prediction on static and dynamic graphs
- Fasted Way! For Free 8 Ball Pool Cash Generator Working 2023 Android Ios
- Featurized HMM
- Feedback effects between similarity and social influence in online communities
- Final-project-review
- Final project presentations 1
- Final project presentations 2
- Finkel and Manning, EMNLP 2009. Nested Named Entity Recognition
- Fire Kirin Money Generator 2023 No Human Verification Get Free Money (Working Method)
- Flick dataset
- Flickr
- Florencia Reali and Thomas L. Griffiths, Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift, Proceedings of The Royal Society of London. Series B, Biological Sciences 2010
- Football networks
- Forest Fire
- Forest Fire Model
- Forest Fire graph generation