Papers
Correlation Clustering and Biclustering with Locally Bounded Errors
Gregory Puleo, Olgica Milenkovic
Cross-Graph Learning of Multi-Relational Associations
Hanxiao Liu, Yiming Yang
CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy
Ran Gilad-Bachrach, Nathan Dowlin, Kim Laine et al.
Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control
Prashanth L.A., Cheng Jie, Michael Fu et al.
Data-driven Rank Breaking for Efficient Rank Aggregation
Ashish Khetan, Sewoong Oh
Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning
Philip Thomas, Emma Brunskill
DCM Bandits: Learning to Rank with Multiple Clicks
Sumeet Katariya, Branislav Kveton, Csaba Szepesvari et al.
Dealbreaker: A Nonlinear Latent Variable Model for Educational Data
Andrew Lan, Tom Goldstein, Richard Baraniuk et al.
Deconstructing the Ladder Network Architecture
Mohammad Pezeshki, Linxi Fan, Philemon Brakel et al.
Deep Gaussian Processes for Regression using Approximate Expectation Propagation
Thang Bui, Daniel Hernandez-Lobato, Jose Hernandez-Lobato et al.
Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin
Dario Amodei, Sundaram Ananthanarayanan, Rishita Anubhai et al.
Deep Structured Energy Based Models for Anomaly Detection
Shuangfei Zhai, Yu Cheng, Weining Lu et al.
Dictionary Learning for Massive Matrix Factorization
Arthur Mensch, Julien Mairal, Bertrand Thirion et al.
Differential Geometric Regularization for Supervised Learning of Classifiers
Qinxun Bai, Steven Rosenberg, Zheng Wu et al.
Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing
Marco Gaboardi, Hyun Lim, Ryan Rogers et al.
Differentially Private Policy Evaluation
Borja Balle, Maziar Gomrokchi, Doina Precup
Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data
Sandhya Prabhakaran, Elham Azizi, Ambrose Carr et al.
Discrete Deep Feature Extraction: A Theory and New Architectures
Thomas Wiatowski, Michael Tschannen, Aleksandar Stanic et al.
Discrete Distribution Estimation under Local Privacy
Peter Kairouz, Keith Bonawitz, Daniel Ramage
Discriminative Embeddings of Latent Variable Models for Structured Data
Hanjun Dai, Bo Dai, Le Song
Distributed Clustering of Linear Bandits in Peer to Peer Networks
Nathan Korda, Balazs Szorenyi, Shuai Li
Diversity-Promoting Bayesian Learning of Latent Variable Models
Pengtao Xie, Jun Zhu, Eric Xing
Domain Adaptation with Conditional Transferable Components
Mingming Gong, Kun Zhang, Tongliang Liu et al.
Doubly Decomposing Nonparametric Tensor Regression
Masaaki Imaizumi, Kohei Hayashi
Doubly Robust Off-policy Value Evaluation for Reinforcement Learning
Nan Jiang, Lihong Li