May 18, 2015
New England Machine Learning Day 2015
9:00 AM
Location: Cambridge, MA, USA
Poster Title |
Presenting Author/ Complete List of Authors |
| Supersparse Linear Integer Models for Optimized Medical Scoring Systems | Berk Ustun, MIT/Berk Ustun, Cynthia Rudin |
| A Robotic Grasping System With Bandit-Based Adaptation
|
John Oberlin, Brown University/John Oberlin, Stefanie Tellex |
| Reliable and scalable variational inference for the hierarchical Dirichlet process
|
Michael C. Hughes, Brown University/Michael C. Hughes, Dae Il Kim, Erik B. Sudderth |
| Learning Propositional Functions in Large State Spaces for Planning and Reinforcement Learning
|
David Hershkowitz, Brown University, Computer Science Department (undergrad)/D. Ellis Hershkowitz, James MacGlashan, Stefanie Tellex |
| Optimization as Estimation with Gaussian Process Bandits | Zi Wang, CSAIL, MIT/Zi Wang, Stefanie Jegelka, Leslie Pack Kaelbling, Tomás Lozano-Pérez
|
| Estimating the Partition Function by Discriminance Sampling
|
Qiang Liu, MIT/Qiang Liu, Jian Peng, Alexander Ihler, John Fisher |
| Preserving Modes and Messages via Diverse Particle Selection | Jason L. Pacheco, Brown/Jason L. Pacheco, Silvia Zuffi, Michael J. Black, Erik B. Sudderth
|
| Data Mining Methods for Analyzing and Modeling Spatiotemporal Data
|
Dawei Wang, UMass Boston/Dawei Wang, Wei Ding, Kui Yu |
| Bayesian Or?s of And?s for Interpretable Classification, with Application to Context-Aware Recommender Systems | Tong Wang, MIT/Tong Wang, Cynthia Rudin, Finale Doshi-Velez, Yimin Liu, Erica Klampfl, Perry MacNeille
|
| Cheap Bandits | Manjesh Hanawal, BU/Manjesh K Hanawal, Venkatesh Saligrama
|
| Modeling and Prediction of Diabetes-Related Hospitalizations Using Electronic Health Records
|
Tingting Xu, BU/Theodora S. Brisimi, Tingting Xu, Ioannis Ch. Paschalidis
|
| Adding Expert Knowledge in Sparse Learning of High Dimensional Diffusion Data in Traumatic Brain Injury
|
Matineh Shaker, Northeastern/Matineh Shaker, Deniz Erdogmus, Jennifer Dy, Sylvain Bouix |
| Machine Learning and Dynamic Programming Algorithms for Motion Planning and Control
|
Oktay Arslan, Georgia Tech/Oktay Arslan, Panagiotis Tsiotras |
| Vector-Valued Property Elicitation
|
Rafael Frongillo, Harvard/Rafael Frongillo, Ian Kash |
| Gradient-based Hyperparameter Optimization through Reversible Learning
|
David Duvenaud, Harvard/Dougal Maclaurin, David Duvenaud, Ryan P. Adams |
| Learning Heterogeneous Progression Patterns of Alzheimer’s Disease with Clustered Hidden Markov Model
|
Chenhui Hu, Harvard/Chenhui Hu, Xiaoxiao Li, Finale Doshi-Velez, Xue Hua, Paul Thompson, Georges Fakhri, Quanzheng Li |
| Exploring Collections with Interactive Spatial Organization
|
Kenneth C. Arnold, Harvard/Kenneth C. Arnold, Krzysztof Z. Gajos |
| ChordRipple: More Creative Chord Recommendations with chord2vec
|
Anna Huang, Harvard/Cheng-Zhi Anna Huang, David Duvenaud, Krzysztof Z. Gajos |
| Stability and optimality in stochastic gradient descent
|
Dustin Tran, Harvard/Dustin Tran, Panos Toulis, Edoardo M. Airoldi |
| Multi-Level Dirichlet Priors for Modelling Topical Variations across Textual Regions | Kriste Krstovski, Harvard-Smithsonian Center for Astrophysics/Kriste Krstovski, David A. Smith, Michael J. Kurtz
|
| Scalable Bayesian Nonparametric Policy Learning in Dec-POMDPs | Miao Liu, MIT LIDS/Miao Liu, Chris Amato, Jonathan P. How
|
| Measuring semantics assumptions
|
Andrea Censi, MIT/Andrea Censi |
| SQUARE: A Benchmark for Consensus Algorithms in Crowdsourcing
|
Matt Lease, University of Texas at Austin/Matthew Lease, Aashish Sheshadri |
| A Nearly-Linear Time Framework for Graph-Structured Sparsity | Chinmay Hegde, MIT/Chinmay Hegde, Piotr Indyk, Ludwig Schmidt
|
| Sample-Optimal Density Estimation in Nearly-Linear Time | Jerry Li, MIT/Jayadev Acharya, Ilias Diakonikolas, Jerry Li, Ludwig Schmidt
|
| A Nearly Optimal and Agnostic Algorithm for Properly Learning a Mixture of k Gaussians, for any Constant k
|
Ludwig Schmidt, MIT/Jerry Li, Ludwig Schmidt |
| Nonparametric Bayesian Inference of Strategy in Infinitely Repeated Games | Max Kleiman-Weiner, MIT/Max Kleiman-Weiner, Penghui Zhou, Joshua B. Tenenbaum
|
| Perturbation Training for Human-Robot Teams
|
Ramya Ramakrishnan, MIT/Ramya Ramakrishnan, Chongjie Zhang, Julie A. Shah |
| Fixed-point algorithms for learning Determinantal Point Processes
|
Zelda Mariet, MIT/Zelda Mariet, Suvrit Sra
|
| Object-based World Modeling with Dependent Dirichlet Process Mixtures
|
Lawson Wong, MIT CSAIL/Lawson L.S. Wong, Thanard Kurutach, Leslie Pack Kaelbling, Tomás Lozano-Pérez |
| Handwritten Tamil Character Recognition using a Convolutional Neural Network
|
Misha Sra, MIT Media lab/Prashanth Vijayaraghavan, Misha Sra |
| Computing Sparse/Low-rank/Structured Optimization Solutions using an Extension of the Frank-Wolfe Method, with Application to Matrix Completion
|
Paul Grigas, MIT Operations Research Center/Robert M. Freund, Paul Grigas, Rahul Mazumder |
| A Sparse Combined Regression-Classification Formulation for Learning a Physiological Alternative to Clinical Post-Traumatic Stress Disorder Scores
|
Sarah Brown, Northeastern University/Sarah Brown, Rami Mangoubi, Andrea Webb, Jennifer Dy |
| RSVP Keyboard A Brain Computer Interface for AAC Technology
|
Paula Gonzalez, Northeastern University/U. Orhan, M. Moghadamfalahi, P. Gonzalez-Navarro, B. Girvent, A. Ahani, M. Haghighi, B. Peters, A. Mooney, A. Fowler, K. Gorman, S. Bedrick, B. Oken, M. Akcakaya, M. Fried-Oken, D. Erdogmus
|
| Personality Prediction in Heterogeneous Social Networks with Incomplete Attributes
|
Yuan Zhong, Northeastern University/Yuan Zhong, Yizhou Sun, Wen Zhong, Rui Dong, Yupeng Gu |
| Clustering and Ranking in Heterogeneous Information Networks via Gamma-Poisson Model
|
Junxiang Chen, Northeastern University/Junxiang Chen, Wei Dai, Yizhou Sun, Jennifer Dy |
| Efficient exploration of large molecular spaces with artificial neural networks
|
Edward Pyzer-Knapp, Harvard/Jos‚ Miguel Hern ndez-Lobato, Edward Pyzer-Knapp, Ryan Adams, Al n Aspuru-Guzik
|
| Sparse Variational Inference for Generalized Gaussian Process Models | Rishit Seth, Tufts University/Rishit Sheth, Bernie Wang, Roni Khardon |
| Method of Moments Learning for Left to Right Hidden Markov Models
|
Cem Sbakan, UIUC CS department/Cem Subakan, Johannes Traa, Paris Smaragdis, Daniel Hsu |
| Concurrent and Incremental Transfer Learning in a Network of Reinforcement Learning Agents | Dan Garant, University of Massachusetts-Amherst/Dan Garant, Bruno Castro da Silva, Victor Lesser, Chongjie Zhang |
| Alternative approaches to discovering causality with additive noise models
|
Kaleigh Clary, University of Massachusetts-Amherst/ Kaleigh Clary, David Jensen
|
| Cancer Subtype Discovery Using Machine Learning | Henry Lo, University of Massachusetts-Boston/Henry Lo, Melissa Cruz, Dawei Wang, Wei Ding, Marieke Kuijjer, Heather Selby, John Quackenbush |
| Inferring Polyadic Events With Poisson Tensor Factorization
|
Aaron Schein, University of Massachusetts-Amherst/Aaron Schein, John Paisley, David M. Blei, Hanna M. Wallach
|
| Towards understanding the Boundary Forest Algorithm | Charles Mathy, Disney Research/Jose Bento, Charles Mathy, Dan Schmidt |
| Predictive Entropy Search for Bayesian Optimization with Unknown Constraints
|
Michael Gelbart, Harvard/Jos‚ Miguel Hern ndez-Lobato, Michael Gelbart, Matt Hoffman, Ryan Adams, Zoubin Ghahramani
|
| Model Selection by Linear Programming
|
Tolga Bolukbasi, BU/Joseph Wang, Tolga Bolukbasi, Kirill Trapeznikov, Venkatesh Saligrama
|
| Bag of Words Approach to Activity Classification | Kevin Amaral, Northeastern/Kevin M. Amaral, Wei Ding, Scott E. Crouter, Ping Chen
|
| NeurOS and NeuroBlocks:ÿ A Neural/Cognitive Operating System and Building Blocks | Lee Scheffler, Cognitivity/Lee Scheffler |
| Feature-Budgeted Random Forest | Feng Nan, Boston University/Feng Nan, Joseph Wang, Venkatesh Saligrama |
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