May 13, 2014

New England Machine Learning Day 2014

Location: Cambridge, MA, USA

Poster Title  Presenting Author/
Complete List of Authors
Inferring Multilateral Relations from Dynamic Bilateral Interactions Aaron Schein / Aaron Schein, Juston Moore, Hanna Wallach
Sparse Neural Networks and Random-Access Pixel Cameras for Energy Efficient Mobile Gaze Tracking Addison Mayberry / Addison Mayberry, Pan Hu, Christopher Salthouse, Benjamin Marlin, Deepak Ganesan
Relational Dependency Networks for Anomaly Detection Amanda Gentzel / Amanda Gentzel, Elisabeth Baseman, Dan Corkill, David Jensen
Dynamically Generated CRFs for Morphological Analysis of Noisy ECG Data Annamalai Natarajan / Annamalai Natarajan, Edward Gaiser, Gustavo Angarita, Robert Malison, Deepak Ganesan, Benjamin Marlin
Generative and Discriminative Models for Improving Noisy Training Data for Relation Extraction Benjamin Roth / Benjamin Roth, Dietrich Klakow
Hierarchical Conditional Random Fields for Outlier Detection: An Application to Detecting Epileptogenic Cortical Malformations Bilal Ahmed / Bilal Ahmed, Thomas Thesen, Karen Blackmon, Orrin Devinsky, Ruben Kuzniecky, and Carla E. Brodley
Boundary algorithm for fast online classification and regression Charles Mathy / Charles Mathy, Nate Derbinsky, Jose Bento, Jonathan Rosenthal, Jonathan Yedidia
Best Response Bayesian Reinforcement Learning for Multiagent Systems with State Uncertainty Chris Amato / Frans A. Oliehoek and Christopher Amato
Learning Dirichlet Priors for Affordance Aware Planning David Abel and Gabriel Barth-Maron / David Abel, Gabriel Barth-Maron, James MacGlashan, Stefanie Tellex
Learning with Mixtures of Dependency Networks David Arbour / David Arbour, David Jensen
Employment of Frank-Wolfe algorithm to perform marginal inference in a Gibbs distribution David Belanger
Restricted Memory Online Variational Bayesian Changepoint Detection Diana Cai / Diana Cai, Ryan Adams
Learning Modular Structures from Network Data and Node Variables Elham Azizi / Elham Azizi, Edoardo M. Airoldi, James E. Galagan
Dynamic Statistical Models of Collective Social Network Behavior Elisabeth Baseman / Elisabeth Baseman, Stephen Judd, Michael Kearns, David Jensen
Fast Margin-based Cost-sensitive Classification Feng Nan / Feng Nan, Joseph Wang, Kirill Trapeznikov, Venkatesh Saligrama
Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Noisy Matrix Decomposition Hanie Sedghi
Augur: a Modeling Language for Data-Parallel Probabilistic Inference Jean-Baptiste Tristan / Jean-Baptiste Tristan, Daniel Huang, Joseph Tassarotti, Adam Pocock, Stephen J. Green, Guy L. Steele Jr
Connected Sub-graph Detection Jing Qian / Jing Qian, Venkatesh Saligrama, Yuting Chen
An information-theoretic analysis of resampling in sequential Monte Carlo Jonathan Huggins / Jonathan H. Huggins and Daniel M. Roy
Text analysis techniques for nominating contact offenders in peer-to-peer file sharing networks Juston Moore / Juston Moore, Brian Levine, Marc Liberatore, Hanna Wallach, Janis Wolak
A Sound and Complete Algorithm for Learning Causal Models from Relational Data Katerina Marazopoulou / Marc Maier, Katerina Marazopoulou, David Arbour, David Jensen
Time Series Analysis of Mobile Data Usage Reveals Geographic Location Keen Sung / Keen Sung, Erik Learned-Miller, Brian Levine, Marc Liberatore
Evaluating Topic Models through Histogram Analysis Kriste Krstovski / Kriste Krstovski, David A. Smith and Michael J. Kurtz
A Graphical Model for Entity-based Document Retrieval Laura Dietz / Laura Dietz, Jeffrey Dalton, Bruce Croft
Classifier-Adjusted Density Estimation for Anomaly Detection and One-Class Lisa Friedland / Lisa Friedland, Amanda Gentzel, David Jensen
Learning of Overcomplete Latent Variable Models: Supervised and Semi-supervised Settings Majid Janzamin
Tensor Factorization for Large-Scale Relational Learning Maximilian Nickel / Maximilian Nickel, Volker Tresp
Person Re-Identification using Kernel-based Metric Learning Methods Mengran Gou / Fei Xiong, Mengran Gou, Octavia Camps, Mario Sznaier
Regression with No Labeled Data Mohammad Gheshlaghi Azar / Mohammad Gheshlaghi Azar and Konrad Kording
Inferring Helpful Actions Nakul Gopalan / Nakul Gopalan, Izaak Baker, Stefanie Tellex
DISCOMAX: Distance Correlation Maximization using Graph Laplacians Praneeth Vepakomma / Praneeth Vepakomma, Chetan Tonde, Ahmed Elgammal
Towards Collaborative Filtering Recommender Systems for Tailored Health Communications Roy Adams
Deterministic Feature Selection for Linear Support Vector Machines Saurabh Paul / Saurabh Paul, Malik Magdon-Ismail and Petros Drineas
The Value of Temporal Data for Learning Influence Networks Spyros Zoumpoulis / Munther Dahleh, John Tsitsiklis, Spyros Zoumpoulis
Co-Planning via Inverse Reinforcement Learning Stephen Brawner / Stephen Brawner, Lee Painton, Stefanie Tellex, Michael Littman
A Kernel-Based Framework for Learning with Irregularly Sampled Physiological Time Series Steve Li
Gradient-based inference for higher-order probabilistic programming languages Tianlin Shi / Alexey Radul, Vikash K. Mansinghka
Sensing-Aware kernel SVMs Weicong Ding / Weicong Ding, Prakash Ishwar, Venkatesh Saligrama, W. Clem Karl
Authorship attribution of unsigned Supreme Court opinions William Li / William Li, Pablo Azar, David Larochelle, Phil Hill, James Cox, Robert C. Berwick, Andrew W. Lo
Modeling and Prediction of Heart-Related Hospitalization Using Electronic Health Records Data Wuyang Dai / Wuyang Dai, Theodora Brisimi, Venkatesh Saligrama, Ioannis Ch. Paschalidis
Learning dynamic spatiotemporal fields using data from mobile sensors Xiaodong Lan / Xiaodong Lan and Mac Schwager
Handling Physician Subjectivity in the Prediction of Disease Course: An Application to Multiple Sclerosis Yijun Zhao / Yijun Zhao, Carla Brodley, Tanuja Chitnis, Brian C. Healy
A Convex Moments-based Approach to Subspace Clustering with Priors Yin Wang / Yin Wang, Yongfang Cheng, Mario Sznaier, Octavia Camps
Formal Methods for Learning and Detection of Anomalous Behavior in Cyber-Physcial Systems Zhaodan Kong / Zhaodan Kong, Austin Jones, Calin Belta

For any questions, please contact MLday14@microsoft.com.