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Submissions from 2015

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Commitment Without Regrets: Online Learning in Stackelberg Security Games, Maria-Florina Balcan, Avrim Blum, Nika Haghtalab, and Ariel D. Procaccia

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Learning Cooperative Games, Maria-Florina Balcan, Ariel D. Procaccia, and Yair Zick

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Active Learning – Modern Learning Theory, Maria-Florina Balcan and Ruth Urner

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Decomposition-Based Optimal Market-Based Planning for Multi-Agent Systems with Shared Resources, Sue Ann Hong and Geoffrey J. Gordon

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Fast Function to Function Regression, Junier B. Oliva, Willie Neiswanger, Barnabas Poczos, Erik P. Xing, and Jeff Schneider

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Two-stage sampled learning theory on distributions, Zoltan Szabo, Arthur Gretton, Barnabas Poczos, and Bharath Sriperumbudur

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Column Subset Selection with Missing Data via Active Sampling, Yining Wang and Aarti Singh

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Noise-adaptive Margin-based Active Learning and Lower Bounds under Tsybakov Noise Condition, Yining Wang and Aarti Singh

Submissions from 2014

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Center Based Clustering: A Foundational Perspective, Pranjal Awasthi and Maria-Florina Balcan

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The Power of Localization for Efficiently Learning Linear Separators with Noise, Pranjal Awasthi, Maria-Florina Balcan, and Philip M. Long

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Feature Selection For High-Dimensional Clustering, Martin Azizyan, Aarti Singh, and Larry Wasserman

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Efficient Representations for Life-Long Learning and Autoencoding, Maria-Florina Balcan, Avrim Blum, and Santosh Vempala

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Statistical Active Learning Algorithms for Noise Tolerance and Differential Privacy, Maria-Florina Balcan and Vitaly Feldman

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Robust Hierarchical Clustering, Maria-Florina Balcan, Yingyu Liang, and Pramod Gupta

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FlexiFaCT: Scalable Flexible Factorization of Coupled Tensors on Hadoop, Alex Beutel, Abhimanu Kumar, Evangelos E. Papalexakis, Partha Pratim Talukdar, Christos Faloutsos, and Eric P. Xing

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On the Bootstrap for Persistence Diagrams and Landscapes, Frederic Chazal, Brittany Therese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Aarti Singh, and Larry Wasserman

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Exploiting bounded staleness to speed up Big Data analytics, Henggang Cui, James Cipar, Qirong Ho, Jin Kyu Kim, Seunghak Lee, Abhimanu Kumar, Jinliang Wei, Wei Dai, Gregory R. Ganger, Phillip B. Gibbons, Garth Gibson, and Eric P. Xing

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Scalable Kernel Methods via Doubly Stochastic Gradients, Bo Dai, Bo Xie, Niao He, Yingyu Liang, Anant Raj, Maria-Florina Balcan, and Le Song

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Parallel Markov Chain Monte Carlo for Pitman-Yor Mixture Models, Avinava Dubey, Sinead Williamson, and Eric P. Xing

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Dependent nonparametric trees for dynamic hierarchical clustering, Kumar Dubey, Qirong Ho, Sinead Williamson, and Eric P. Xing

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Diffusion of Lexical Change in Social Media, Jacob Eisenstein, Brendan O'Connor, Noah A. Smith, and Eric P. Xing

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Confidence Sets for Persistence Diagrams, Brittany Therese Fasy, Fabrizio Lecci, Alessandro Rinaldo, Larry Wasserman, Sivaraman Balakrishnan, and Aarti Singh

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Incorporating Vector Space Similarity in Random Walk Inference over Knowledge Bases, Matt Gardner, Partha Pratim Talukdar, Jayant Krishnamurthy, and Tom Mitchell

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Fast and Improved SLEX Analysis of High-dimensional Time Series, Ahmed Hefny, Robert E. Kass, Sanjeev Khanna, Matthew Smith, and Geoffrey J. Gordon

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On Modeling Community Behaviors and Sentiments in Microblogging, Tuan-Anh Hoang, William W. Cohen, and Ee-Peng Lim

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Modeling Large Social Networks in Context, Qirong Ho

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Joint Summarization of Large-scale Collections of Web Images and Videos for Storyline Reconstruction, Gunhee Kim, Leonid Sigal, and Eric P. Xing

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Reconstructing Storyline Graphs for Image Recommendation from Web Community Photos, Gunhee Kim and Eric P. Xing

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Graph Estimation From Multi-Attribute Data, Mladen Kolar, Han Liu, and Eric P. Xing

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Statistical Modeling of Student Performance to Improve Chinese Dictation Skills with an Intelligent Tutor, John W. Kowalski, Yanhui Zhang, and Geoffrey J. Gordon

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Subspace Learning from Extremely Compressed Measurements, Akshay Krishnamurthy, Martin Azizyan, and Aarti Singh

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Nonparametric Estimation of Renyi Divergence and Friends, Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos, and Larry Wasserman

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On Estimating L_2^2 Divergence, Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos, and Larry Wasserman

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On the Power of Adaptivity in Matrix Completion and Approximation, Akshay Krishnamurthy and Aarti Singh

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Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data, Abhimanu Kumar, Alex Beutel, Qirong Ho, and Eric P. Xing

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On Model Parallelization and Scheduling Strategies for Distributed Machine Learning, Seunghak Lee, Jin Kyu Kim, Xun Zheng, Qirong Ho, Garth Gibson, and Eric P. Xing

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Screening Rules for Overlapping Group Lasso, Seunghak Lee and Eric P. Xing

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Influence Function Learning in Information Diffusion Networks, Yingyu Liang, Nan Du, Maria-Florina Balcan, and Le Song

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A Tale of Two Entity Linking and Discovery Systems, Kathryn Mazaitis, Richard C. Wang, Frank Lin, Bhavana Dalvi, Jakob Bauer, and William W. Cohen

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Modeling Citation Networks using Latent Random Offsets, Willie Neiswanger, Chong Wang, Qirong Ho, and Eric P. Xing

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Asymptotically Exact, Embarrassingly Parallel MCMC, Willie Neiswanger, Chong Wang, and Eric P. Xing

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The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling, Willie Neiswanger, Frank Wood, and Eric P. Xing

A Machine Learning Approach for Dynamical Mass Measurements of Galaxy Clusters, Michelle Ntampaka, Hy Trac, D. J. Sutherland, N. Battaglia, Barnabas Poczos, and Jeff Schneider

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Statistical Text Analysis for Social Science, Brendan T. O'Connor

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FuSSO: Functional Shrinkage and Selection Operator, Junier B. Oliva, Barnabas Poczos, Timothy Verstynen, Aarti Singh, Jeff Schneider, Fang-Cheng Yeh, and Wen-Yih Isaac Tseng

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Turbo-SMT: Accelerating Coupled Sparse Matrix-Tensor Factorizations by 200x, Evangelos E. Papalexakis, Christos Faloutsos, Tom Mitchell, Partha Pratim Talukdar, Nicholas D. Sidiropoulos, and Brian Murphy

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Network Analysis of Breast Cancer Progression and Reversal Using a Tree-Evolving Network Algorithm, Ankur P. Parikh, Ross E. Curtis, Irene Kuhn, Sabine Becker-Weimann, Mina Bissell, Eric P. Xing, and Wei Wu

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Language Modeling with Power Low Rank Ensembles, Ankur P. Parikh, Avneesh Saluja, Chris Dyer, and Eric P. Xing

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Robust Reverse Engineering of Dynamic Gene Networks Under Sample Size Heterogeneity, Ankur P. Parikh, Wei Wu, and Eric P. Xing

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An Analysis of Active Learning With Uniform Feature Noise, Aaditya Ramdas, Barnabas Poczos, Aarti Singh, and Larry Wasserman

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On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives, Aaditya Ramdas, Sashank J. Reddi, Barnabas Poczos, Aarti Singh, and Larry Wasserman

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k-NN Regression on Functional Data with Incomplete Observations, Sashank J. Reddi and Barnabas Poczos

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Doubly Robust Covariate Shift Correction, Sashank J. Reddi, Barnabas Poczos, and Alex Smola

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On the Decreasing Power of Kernel and Distance based Nonparametric Hypothesis Tests in High Dimensions, Sashank J. Reddi, Aaditya Ramdas, Barnabas Poczos, Aarti Singh, and Larry Wasserman

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Effects of Sample Selection Bias on the Accuracy of Population Structure and Ancestry Inference, Suyash Shringarpure and Eric P. Xing

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Exponential Concentration of a Density Functional Estimator, Shashank Singh and Barnabas Poczos

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Generalized Exponential Concentration Inequality for Renyi Divergence Estimation, Shashank Singh and Barnabas Poczos

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Nonparametric Latent Tree Graphical Models: Inference, Estimation, and Structure Learning, Le Song, Han Liu, Ankur P. Parikh, and Eric P. Xing

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Scaling Graph-based Semi Supervised Learning to Large Number of Labels Using Count-Min Sketch, Partha Pratim Talukdar and William W. Cohen

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Dependency Parsing for Weibo: An Efficient Probabilistic Logic Programming Approach, William Yang Wang, Lingpeng Kong, Kathryn Mazaitis, and William W. Cohen

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Consistent Bounded-Asynchronous Parameter Servers for Distributed ML, Jinliang Wei, Wei Dai, Abhimanu Kumar, Xun Zheng, Qirong Ho, and Eric P. Xing

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Large Scale Distributed Multiclass Logistic Regression, Pengtao Xie, Jin Kyu Kim, and Eric P. Xing

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GWAS in a Box: Statistical and Visual Analytics of Structured Associations via GenAMap, Eric P. Xing, Ross E. Curtis, Georg Schoenherr, Seunghak Lee, Junming Yin, Kriti Puniyani, Wei Wu, and Peter Kinnaird

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LightLDA: Big Topic Models on Modest Compute Clusters, Jinhui Yuan, Fei Gao, Quirong Ho, Jinliang Wei, Xun Zheng, Eric P. Xing, Tie-Yan Liu, and Wei-Ying Ma

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Towards Scalable Analysis of Images and Videos, Bin Zhao

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Hierarchical Feature Hashing for Fast Dimensionality Reduction, Bin Zhao and Eric P. Xing

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Quasi Real-Time Summarization for Consumer Videos, Bin Zhao and Eric P. Xing

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Model-Parallel Inference for Big Topic Models, Xun Zheng, Jin Kyu Kim, Qirong Ho, and Eric P. Xing

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Bayesian Inference with Posterior Regularization and Applications to Infinite Latent SVMs, Jun Zhu, Ning Chen, and Eric P. Xing

Submissions from 2013

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Scalable Dynamic Nonparametric Bayesian Models of Content and Users, Amr Ahmed and Eric P. Xing

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Approximation Algorithms and New Models for Clustering and Learning, Pranjal Awasthi

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Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation, Martin Azizyan, Aarti Singh, and Larry Wasserman

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Recovering Block-structured Activations Using Compressive Measurements, Sivaraman Balakrishnan, Mladen Kolar, Alessandro Rinaldo, and Aarti Singh

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Cluster Trees on Manifolds, Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, and Larry Wasserman

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Regularization of Latent Variable Models to Obtain Sparsity, Ramnath Balasubramanyan and William W. Cohen

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From Topic Models to Semi-Supervised Learning: Biasing Mixed-membership Models to Exploit Topic-Indicative Features in Entity Clustering, Ramnath Balasubramanyan, Bhavana Dalvi, and William W. Cohen

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Active and passive learning of linear separators under log-concave distributions, Maria-Florina Balcan and Philip M. Long

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A Spectral Learning Approach to Range-Only SLAM, Byron Boots and Geoffrey J. Gordon

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Hilbert Space Embeddings of Predictive State Representations, Byron Boots, Arthur Gretton, and Geoffrey J. Gordon

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Learning Large-Scale Conditional Random Fields, Joseph K. Bradley

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Statistical Models and Algorithms for Studying Hand and Finger Kinematics and their Neural Mechanisms, Lucia Castellanos

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Learning with Sparcity: Structures, Optimization and Applications, Xi Chen

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Solving the Straggler Problem with Bounded Staleness, James Cipar, Qirong Ho, Jin Kyu Kim, Seunghak Lee, Gregory R. Ganger, Garth Gibson, Kimberly Keeton, and Eric P. Xing

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Petuum: A Framework for Iterative-Convergent Distributed ML, Wei Dai, Jinliang Wei, Jin Kyu Kim, Seunghak Lee, Junming Yin, Qirong Ho, and Eric P. Xing

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Very Fast Similarity Queries on Semi-Structured Data from the Web, Bhavana Dalvi and William W. Cohen

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Exploratory Learning, Bhavana Dalvi, William W. Cohen, and Jamie Callan

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A nonparametric mixture model for topic modeling over time, Avinava Dubey, Ahmed Hefny, Sinead Williamson, and Eric P. Xing

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Improving Learning and Inference in a Large Knowledge-base using Latent Syntactic Cues, Matt Gardner, Partha Pratim Talukdar, Bryan Kisiel, and Tom Mitchell

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Politics, Sharing and Emotion in Microblogs, Tuan-Anh Hoang, William W. Cohen, Ee-Peng Lim, Douglas Pierce, and David P. Redlawsk

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More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server, Qirong Ho, James Cipar, Henggang Cui, Jin Kyu Kim, Seunghak Lee, Phillip B. Gibbons, Garth Gibson, Gregory R. Ganger, and Eric P. Xing

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Exploiting Non-Sequence Data in Dynamic Model Learning, Tzu-Kuo Huang

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Jointly Aligning and Segmenting Multiple Web Photo Streams for the Inference of Collective Photo Storylines, Gunhee Kim and Eric P. Xing

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Uncovering Structure in High-Dimensions: Networks and Multi-task Learning Problems, Mladen Kolar

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Markov Network Estimation From Multi-attribute Data, Mladen Kolar, Han Liu, and Eric P. Xing

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Recovering Graph-Structured Activations using Adaptive Compressive Measurements, Akshay Krishnamurthy, James Sharpnack, and Aarti Singh

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Low-Rank Matrix and Tensor Completion via Adaptive Sampling, Akshay Krishnamurthy and Aarti Singh

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Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models, Jayant Krishnamurthy and Tom Mitchell

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Probabilistic Models for Collecting, Analyzing, and Modeling Expression Data, Hai-Son Phuoc Le

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Discovering Student Models with a Clustering Algorithm Using Problem Content, Nan Li, William W. Cohen, and Kenneth R. Koedinger

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General and Efficient Cognitive Model Discovery Using a Simulated Student, Nan Li, Eliane Stampfer, William W. Cohen, and Kenneth R. Koedinger