Semi-Supervised Learning with Competitive Infection Models<\/div><\/td>\r\n
\r\nNir Rosenfeld, Harvard University\/Amir Globerson, Tel Aviv University<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nMultiscale Semi-Markov Dynamics for Intracortical Brain-Computer Interfaces<\/div><\/td>\r\n Daniel J Milstein, Brown University\/ H.T. Kung, Harvard University; Jason L Pacheco, MITLeigh R Hochberg, Brown & MGH & VA & Harvard, John D Simeral, Brown & MGH & VABeata Jarosiewicz, NeuroPaceErik B Sudderth, UV Irvine & Brown<\/td>\r\n<\/tr>\r\n | \r\n\r\nBreaking the n^{-1\/2} barrier for permutation-based ranking models<\/div><\/td>\r\n \r\nCheng Mao, MIT\/Jonathan Weed, MIT; Philippe Rigollet, MIT; Ashwin Pananjady UC Berkeley; Martin J. Wainwright, UC Berkeley<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nApplication of Breiman and Cutler\u2019s Random Forest Algorithm for Identification of Mutated Genes Responsible for Drug Resistance in M. Tuberculosis Strains<\/div><\/td>\r\n \r\n\r\n\r\nUma Girkar, MIT\/ Ling TengHarvard Medical School; Dr. Gil Alterovitz, Harvard Medical School\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nBayesian Nonparametrics in Julia<\/div><\/td>\r\n Vadim Smolyakov, MIT\/ John W. Fisher III, MIT<\/td>\r\n<\/tr>\r\n | \r\n\r\nAn Epidemic Modeling Framework For Hashtag Diffusion on Congressional Twitter Networks<\/div><\/td>\r\n \r\n\r\n\r\nCantay Caliskan, Boston University\/ Dino P. Christenson, Boston University\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nInference and Learning in Latent Count Models<\/div><\/td>\r\n Kevin Winner, UMass Amherst\/Dan Sheldon, Professor, UMass Amherst, Mt. Holyoke College<\/td>\r\n<\/tr>\r\n | \r\n\r\nCombating Imbalanced Data with Generative Adversarial Networks<\/div><\/td>\r\n \r\nRheeya Uppaal, UMass Amherst<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nStochastic dynamics of sensory cortical neurons underlie taste-related decision making<\/div><\/td>\r\n Narendra Mukherjee, Brandeis University\/ Joseph Wachutka, Brandeis University; Donald B Katz, Brandeis University<\/td>\r\n<\/tr>\r\n | \r\n\r\nJoint Event Detection and Description in Continuous Video Streams<\/div><\/td>\r\n \r\n\r\n\r\nHuijuan Xu, Boston University\/ Boyang Li, Liulishuo Silicon Valley AI; LabVasili Ramanishka, Boston University; Leonid Sigal, University of British Columbia; Kate Saenko, Boston University\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nWhen Life Gives you Lemmas, Make an Cross-Document Event Coreference Resolution System<\/div><\/td>\r\n Chris Tanner, Brown University\/Eugene Charniak, Brown University<\/td>\r\n<\/tr>\r\n | \r\n\r\nDissociating Linguistic Form and Meaning with Adversarial-Motivational Training<\/div><\/td>\r\n \r\n\r\n\r\nAlexey Romanov, University of Massachussetts\/ Anna R., University of Massachusetts Lowell; Anna R., University of Massachusetts Lowell; David D., University of Massachusetts Lowell\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nEarly Syntactic Bootstrapping in an Incremental Memory-Limited Word Learner<\/div><\/td>\r\n Sepideh Sadeghi, Tufts University\/ Sepideh S., Tufts University; Matthias S., Tufts University<\/td>\r\n<\/tr>\r\n | \r\n\r\nSynthetic and Natural Noise Both Break Neural Machine Translation<\/div><\/td>\r\n \r\n\r\n\r\nYonatan Belinkov, MIT\/ Yonatan Bisk, University of Washington\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nUnbiased Hamiltonian Monte Carlo with couplings<\/div><\/td>\r\n Jeremy Heng, Harvard University\/ Pierre Jacob, Harvard University<\/td>\r\n<\/tr>\r\n | \r\n\r\nState Abstractions for Lifelong Reinforcement Learning<\/div><\/td>\r\n \r\n\r\n\r\nDavid Abel, Brown University\/ Dilip Arumugam, Brown University; Lucas Lehnert, Brown University; Michael L. Littman, Brown University\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nPolicy and Value Transfer for Lifelong Reinforcement Learning<\/div><\/td>\r\n Yuu Jinnai, Brown University\/ David Abel, Brown University; George Konidaris, Brown University; Michael Littman, Brown University; Yue Gao, Brown University<\/td>\r\n<\/tr>\r\n | \r\n\r\nA Robust Learning Algorithm for Regression Models Using Distributionally Robust Optimization under the Wasserstein Metric<\/div><\/td>\r\n \r\nRuidi Chen, Boston University\/ Ioannis Ch. Paschalidis, Boston University<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nGeneralizing Bottleneck Problems<\/div><\/td>\r\n Hsiang Hsu, Harvard University\/ Shahab Asoodeh, University of Chicago; Salman Salamatian, MIT; Flavio P. Calmon, Harvard University<\/td>\r\n<\/tr>\r\n | \r\n\r\nLimits of Learning to Reduce Incompleteness in Partially Observed Networks<\/div><\/td>\r\n \r\n\r\n\r\nTimothy LaRock, Northeastern University\/ Sahely Bhadra, Indian Institute of Technology; Tina Eliassi-Rad, Northeastern University\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nDistributing Frank-Wolfe via Map-Reduce<\/div><\/td>\r\n Armin Moharrer, Northeastern University\/ Stratis Ioannidis, Northeastern University<\/td>\r\n<\/tr>\r\n | \r\n\r\nNon-Parametric Inference for Gaussian Process<\/div><\/td>\r\n \r\n\r\n\r\nLinfeng Liu, Tufts University\/ Liping Liu., Tufts University\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nOn the Sample Complexity of Adversarially Robust Generalization<\/div><\/td>\r\n Dimitris Tsipras, MIT\/ Shibani Santurkar, MIT; Ludwig Schmidt, MIT; Kunal Talwar, Google; Aleksander Madry, MIT<\/td>\r\n<\/tr>\r\n | \r\n\r\nOptimality of Approximate Inference Algorithms on Stable Instances<\/div><\/td>\r\n \r\nHunter Lang, MIT\/ David Sontag, MIT; Aravindan Vijayaraghavan, Northwestern University<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nGraph Distance from the Topological Perspective of Nonbacktracking Cycles<\/div><\/td>\r\n Leo Torres, Northeastern University\/ Tina Eliassi-Rad, Northeastern University<\/td>\r\n<\/tr>\r\n | \r\n\r\nCorrelation-based Time Series Analytics<\/div><\/td>\r\n \r\n\r\n\r\nRamoza Ahsan, Worcester Polytechnic Institute\/ Rodica Neamtu, Worcester Polytechnic Institute; Muzammil Bashir, Worcester Polytechnic Institute; Elke Rundensteiner, Worcester Polytechnic Institute; Garbor Sarkozy, Worcester Polytechnic Institute\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nLearning Deep Embeddings by Learning to Rank<\/div><\/td>\r\n Kun He, Boston University\/ Fatih Cakir, First Fuel Software; Sarah Adel Bargal, Boston University; Stan Sclaroff, Boston University; Yan Lu, Amazon Lab126<\/td>\r\n<\/tr>\r\n | \r\n\r\nLearning Disentangled Representations of Texts with Application to Biomedical Abstracts<\/div><\/td>\r\n \r\n\r\n\r\nSarthak Jain, Northeastern University\/ Edward Banner, CCIS, Northeastern University; Jan-Willem van de Meent, Northeastern University; Iain J Marshall, King's College London; Byron C Wallace, CCIS, Northeastern University\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nTime Series Analysis via Matrix Estimation<\/div><\/td>\r\n Anish Agarwal, MIT\/ Muhammad Jehangir Amjad, MIT; Devavrat Shah, MIT; Dennis Shen, MIT<\/td>\r\n<\/tr>\r\n | \r\n\r\nWhy did they cite that?<\/div><\/td>\r\n \r\n\r\n\r\nCharles Lovering, Worcester Polytechnic Institute\/ Jake Whitehill, WPI\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nCommittee-Based Anomaly Detection with Explanations<\/div><\/td>\r\n Leilani H. Gilpin, MIT\/ Gerald Jay Sussman, MIT<\/td>\r\n<\/tr>\r\n | \r\n\r\nMultiagent Norm Identification: A Belief-Theoretic Approach for Automatically Identifying Explicitly Represented Norms from Observation<\/div><\/td>\r\n \r\n\r\n\r\nVasanth Sarathy, Tufts University\/ Matthias Scheutz, Tufts University\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nImproving Emotion Detection with Sub-clip Classification Boosting<\/div><\/td>\r\n Ermal Toto, Worcester Polytechnic Institute\/ Brandon F. WPI; Elke R., WPI<\/td>\r\n<\/tr>\r\n | \r\n\r\nDistributionally Robust Submodular Maximization<\/div><\/td>\r\n \r\n\r\n\r\nMatthew Staib, MIT\/ Bryan Wilder, USC; Stefanie Jegelka, MIT\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nExperimental Design under Bradley Terry Model<\/div><\/td>\r\n Yuan Guo, Northeastern University\/ Peng Tian Northeastern University; Jayashree Kalpathy-Cramer, Harvard Medical School; Susan Ostmo, Oregon Health & Science University; J. Peter Campbell, Oregon Health & Science University; Michael F.Chiang, Oregon Health & Science University; Deniz Erdogmus, Northeastern University; Jennifer Dy, Northeastern University; Stratis Ioannidis, Northeastern University<\/td>\r\n<\/tr>\r\n | \r\n\r\nDeep Learning for Optimal Filtering<\/div><\/td>\r\n \r\n\r\n\r\nMatt Weiss, Worcester Polytechnic Institute\/ Randy C. Paffenroth, Worcester Polytechnic Institute; Joshua R. Uzarski, U.S. Army NSRDEC; Jacob R. Whitehill, Worcester Polytechnic Institute\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nSeparation of time scales and direct computation of weights in deep neural networks<\/div><\/td>\r\n Nima Dehmamy, Northeastern University\/ Neda Rohani, Northwestern University; Aggelos Katsaggelos, Northwestern University<\/td>\r\n<\/tr>\r\n | \r\n\r\nAn ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks<\/div><\/td>\r\n \r\nPu Zhao, Northeastern University\/ Sijia Liu, IBM research; AIKaidi Xu, Northeastern University; Yanzhi Wang, Northeastern University; Xue Lin, Northeastern University<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nImproving Shape Deformation in Unsupervised Image-to-Image Translation<\/div><\/td>\r\n Aaron Gokaslan, Brown University\/ Vivek Ramanujan, Brown University; Daniel Ritchie, Brown University; Kwang In Kim, University of Bath; James Tompkin, Brown University<\/td>\r\n<\/tr>\r\n | \r\n\r\nLearning in POMDPs with Monte Carlo Tree Search<\/div><\/td>\r\n \r\n\r\n\r\nSammie Katt, Northeastern University\/ Frans A. Oliehoek, University of Liverpool; Christopher Amato, Northeastern University\r\n\r\n<\/div><\/td>\r\n<\/tr>\r\n \r\n\r\nLearning to Place Objects: A Network-based Approach<\/div><\/td>\r\n Xindi Wang, Northeastern University\/ Onur Varol, Northeastern University; Tina Eliassi-Rad, Northeastern University; Albert-L\u00e1szl\u00f3 Barab\u00e1si, Northeastern University<\/td>\r\n<\/tr>\r\n | \r\n\r\n Practical Data-Dependent Metric Compression with Provable Guarantees<\/div><\/td>\r\n | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |