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New England Machine Learning Day 2014

Poster presentation information

  • Setup time starts at 9:00 a.m.
  • Posters may be up to 48"W x 36"H
  • Posters will be adhered to the walls/glass with material we provide (please try to avoid having heavy cardboard posters as this makes it difficult to attach the posters).

The posters will include:

  • Presenting author name
  • Presenting author affiliation/institution
  • Presenting author email address
  • Title
  • Complete list of authors. Please do not list author affiliations
  • Abstract (250 words maximum)

 


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.

 

Date & time

Tuesday, May 13, 2014
Registration and breakfast begin at 9 AM

 

Venue

Microsoft Research New England
Horace Mann Conference Room
First Floor Conference Center
One Memorial Drive, Cambridge, MA

 

Arrival guidance

Upon arrival, be prepared to show a picture ID and sign the Building Visitor Log when approaching the Lobby Floor Security Desk. Alert them to the name of the event you are attending and ask them to direct you to the appropriate floor. The talks will be held the First Floor Conference Center, Horace Mann Conference Room.

Send questions to:
MLday14@microsoft.com