New England Machine Learning Day 2017
Location: Cambridge, MA, USA
| Poster Title | Presenting Author / Authors |
|---|---|
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Robust and Efficient Transfer Learning using Hidden Parameter Markov Decision Processes
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Sam Daulton, Harvard University / Taylor Killian, Harvard University; Finale Doshi-Velez, Harvard University; George Konidaris, Brown University
|
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Multimodal Sparse Representation Learning for Multimedia Applications
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Miriam Cha, Harvard University / Youngjune L. Gwon & H.T. Kung, Harvard University |
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Learning Optimized Risk Scores on Large-Scale Datasets
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Berk Ustun, Massachusetts Institute of Technology / Cynthia Rudin, Duke University
|
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Accurate structure-based drug-protein binding energy prediction with deep convolutional neural networks
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Maksym Korablyov, Massachusetts Institute of Technology / Xiao Luo, Nilai Sarda, Mengyuan Sun, Tyson Chen, Lily Zhang, Ellen Shea, Erica Weng, Brian Xie, Yejin You, Ryan Hays, Shuo Gu, Collin Stultz, & Gil Alterovitz, Harvard-MIT division, Boston Children’s Hospital |
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Kronecker Determinantal Point Processes
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Zelda Mariet, Massachusetts Institute of Technology / Suvrit Sra, Massachusetts Institute of Technology |
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Synthesizing 3D via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative Networks
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Amir Arsalan Soltani, Massachusetts Institute of Technology / Haibin Huang, University of Massachusetts, Amherst; Jiajun Wu, Massachusetts Institute of Technology; Tejas D. Kulkarni, Google DeepMind; Joshua B. Tenenbaum, Massachusetts Institute of Technology |
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R-C3D: Region Convolutional 3D Network for Temporal Activity Detection
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Huijuan Xu, Boston University / Abir Das, Boston University; Kate Saenko, Boston University |
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A Decentralized Cluster Primal Dual Splitting Method for Large-Scale Sparse Support Vector Machines with An Application to Hospitalization Prediction
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Theodora S. Brisimi, Boston University / Alex Olshevsky, Ioannis Ch. Paschalidis, & Wei Shi, Boston University |
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SmartPlayroom: Semi-automated behavioral analysis of children with ASD in naturalistic environment
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Pankaj Gupta, Brown University / Elena Tenenbaum, Stephen Sheinkopf, Thomas Serre, & Dima Amso, Brown University |
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Guided Proofreading of Automatic Segmentations for Connectomics
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Daniel Haehn, Harvard University / Verena Kaynig-Fittkau, Harvard University; James Tompkin, Brown University; Jeff W. Lichtman & Hanspeter Pfister, Harvard University |
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Lie-Access Neural Turing Machines
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Greg Yang, Harvard University / Alexander Rush, Harvard University |
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Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets
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Andrea Tacchetti, Massachusetts Institute of Technology / Stephen Voinea & Georgios Evangelopoulos, Massachusetts Institute of Technology |
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Testing Ising Models
|
Gautam Kamath, Massachusetts Institute of Technology / Constantinos Daskalakis & Nishanth Dikkala, Massachusetts Institute of Technology |
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Mutual Information Hashing
|
Fatih Cakir, Boston University / Kun He, Sarah Adel Bargal, & Stan Sclaroff, Boston University |
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Dataflow Matrix Machines as a Model of Computations with Linear Streams
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Michael Bukatin, HERE North America LLC / Jon Anthony, Boston College |
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A Bandit Framework for Strategic Regression
|
Yang Liu, Harvard University / Yiling Chen, Harvard University |
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Robust Budget Allocation via Continuous Submodular Functions
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Matthew Staib, Massachusetts Institute of Technology / Stefanie Jegelka, Massachusetts Institute of Technology |
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Value Directed Exploration in Multi-Armed Bandits with Structured Priors
|
Bence Cserna, University of New Hampshire / Marek Petrik, Reazul Hasan Russel, & Wheeler Ruml, University of New Hampshire
|
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Designing Neural Network Architectures Using Reinforcement Learning
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Bowen Baker, Massachusetts Institute of Technology / Otkrist Gupta, Nikhil Naik, & Ramesh Raskar, Massachusetts Institute of Technology |
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What do Neural Machine Translation Models Learn about Morphology?
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Yonatan Belinkov, Massachusetts Institute of Technology / Nadir Durrani, Fahim Dalvi, & Hassan Sajjad, Qatar Computing Research Institute; James Glass, Massachusetts Institute of Technology |
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Message-passing algorithms for synchronization problems
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Amelia Perry, Massachusetts Institute of Technology / Alexander S. Wein, Massachusetts Institute of Technology; Afonso S. Bandeira, New York University; Ankur Moitra, Massachusetts Institute of Technology |
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Non-detection in spiked matrix models
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Alex Wein, Massachusetts Institute of Technology / Amelia Perry, Massachusetts Institute of Technology; Afonso Bandeira, New York University Courant; Ankur Moitra, Massachusetts Institute of Technology |
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Coarse-to-Fine Attention Models for Document Summarization
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Jeffrey Ling, Harvard University / Alexander Rush, Harvard University |
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TensorFlow Debugger: Debugging Dataflow Graphs for Machine Learning
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Shanqing Cai, Google / Eric Breck, Eric Nielsen, Michael Salib, & D. Sculley, Google
|
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Computational Prediction of Neoantigens for Personalized Cancer Vaccines
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Michael Rooney, Neon Therapeutics (formerly at Broad, MIT) / Jenn Abelin, Neon Therapeutics (formerly at Broad); Derin Keskin, Dana–Farber Cancer Institute; Sisi Sarkizova, Harvard; Nir Hacohen & Steve Carr, Broad Institute; Cathy Wu, Dana–Farber Cancer Institute |
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On Sequential Elimination Algorithms for Best-Arm Identification in Multi-Armed Bandits
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Shahin Shahrampour, Harvard University / Mohammad Noshad & Vahid Tarokh, Harvard University |
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Bayesian Group Decisions: Algorithms and Complexity
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Amin Rahimian, University of Pennsylvania/MIT Institute for Data, Systems, and Society / Ali Jadbabaie & Elchanan Mossel, Massachusetts Institute of Technology |
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Node Embedding for Network Community Discovery
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Christy Lin, Boston University / Prakash Ishwar, Boston University; Weicong Ding, Technicolor
|
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Max-value Entropy Search for Efficient Bayesian Optimization
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Zi Wang, Massachusetts Institute of Technology / Stefanie Jegelka Professor, Massachusetts Institute of Technology |
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Network Analysis Identifies Regions of Chromosome Interactions in the Genome
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Anastasiya Belyaeva, Massachusetts Institute of Technology / Caroline Uhler, Massachusetts Institute of Technology; Saradha Venkatachalapathy, GV Shivashankar, & Mallika Nagarajan, National University of Singapore |
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SoundNet: Learning Sound Representations from Unlabeled Video
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Carl Vondrick, Massachusetts Institute of Technology / Yusuf Aytar & Antonio Torralba, Massachusetts Institute of Technology |
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Recursive Sampling for the Nystrom Method
|
Christopher Musco, Massachusetts Institute of Technology |
|
Robust Statistics in High Dimensions, Revisited
|
Jerry Li, Massachusetts Institute of Technology / Ilias Diakonikolas, University of Southern California; Gautam Kamath, Massachusetts Institute of Technology; Daniel M. Kane, University of California, San Diego; Ankur Moitra, Massachusetts Institute of Technology; Alistair Stewart, University of Southern California |
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From Patches to Images: A Nonparametric Generative Model
|
Geng Ji, Brown University / Mike Hughes, Harvard University; Erik Sudderth, Brown University/University of California, Irvine |
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Nucleotide-level Modeling of Genetic Regulation with Large Receptive Fields using Dilated Convolutions
|
Ankit Gupta, Harvard University / Alexander Rush, Harvard University |
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Predicting the Quality of Short Narratives from Social Media
|
Tong Wang, University of Massachusetts Boston / Ping C., University of Massachusetts Boston; Albert L., Disney Research
|
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Generative Adversarial Models for Layered Segmentation
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Deniz Oktay, Massachusetts Institute of Technology / Carl Vondrick & Antonio Torralba, Massachusetts Institute of Technology |
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ST-LDDM: An effective model for urban air quality prediction
|
Zheyun Xiao, University of Massachusetts Boston / Yang Mu, Facebook; Wei Ding, University of Massachusetts Boston
|
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Data-driven identification and repair of software vulnerabilities
|
Onur Ozdemir, Draper / Jacob H., Boston University; Louis K., Onur O., Rebecca R., Marc M., Tomo Lazovich, & Jeffrey O., Draper |
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A Non-Linear Spatio-Temporal Modeling Framework for Heavy Precipitation and Crop Yield Prediction
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Yahui Di, University of Massachusetts Boston / Wei Ding, University of Massachusetts Boston |
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Predicting neural response of olfactory system with structural and vibrational properties of molecules
|
Benjamin Sanchez, Harvard University / Aniket Zinzuwadia, Harvard University; Semion Saikin, Harvard University; Honggoo Chae & Dinu F. Albeanu, Cold Spring Harbor Laboratory; Venkatesh N. Murthy & Alán Aspuru-Guzik, Harvard University |
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On Causal Analysis for Heterogeneous Networks
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Katerina Marazopoulou, University of Massachusetts Amherst / David Arbour &
David Jensen, University of Massachusetts Amherst |
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The Ombú estimator: topology of samples to compare distributions
|
Javier Burroni, University of Massachusetts Amherst / David Jensen, University of Massachusetts Amherst |
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A/B Testing in Networks with Adversarial Members
|
Kaleigh Clary, University of Massachusetts Amherst / David Jensen & Andrew McGregor, University of Massachusetts Amherst |
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Scene Grammars, Factor Graphs, and Belief Propagation
|
Jeroen Chua, Brown University / Pedro Felzenszwalb, Brown University |
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Locally Interpretable Models to Generate Annotated Active Learning Recommendations
|
Richard L. Phillips, Haverford College / Kyu Hyun Chang & Sorelle Friedler, Haverford College |
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Crime Hotspot Forecasting via Deep Neural Networks
|
Yong Zhuang, University of Massachusetts Boston / Wei Ding, University of Massachusetts Boston; Melissa Morabito, University of Massachusetts Lowell |