Papers
Manifold Mixup: Better Representations by Interpolating Hidden States
Vikas Verma, Alex Lamb, Christopher Beckham et al.
Probabilistic Neural Symbolic Models for Interpretable Visual Question Answering
Ramakrishna Vedantam, Karan Desai, Stefan Lee et al.
Learning Dependency Structures for Weak Supervision Models
Paroma Varma, Frederic Sala, Ann He et al.
Model Comparison for Semantic Grouping
Francisco Vargas, Kamen Brestnichki, Nils Hammerla
Composing Value Functions in Reinforcement Learning
Benjamin Van Niekerk, Steven James, Adam Earle et al.
Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD
Marten Van Dijk, Lam Nguyen, Phuong Ha Nguyen et al.
Large-Scale Sparse Kernel Canonical Correlation Analysis
Viivi Uurtio, Sahely Bhadra, Juho Rousu
Fairness without Harm: Decoupled Classifiers with Preference Guarantees
Berk Ustun, Yang Liu, David Parkes
Distributed, Egocentric Representations of Graphs for Detecting Critical Structures
Ruo-Chun Tzeng, Shan-Hung Wu
Metropolis-Hastings Generative Adversarial Networks
Ryan Turner, Jane Hung, Eric Frank et al.
Homomorphic Sensing
Manolis Tsakiris, Liangzu Peng
Learning Hawkes Processes Under Synchronization Noise
William Trouleau, Jalal Etesami, Matthias Grossglauser et al.
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
Brian Trippe, Jonathan Huggins, Raj Agrawal et al.
DeepNose: Using artificial neural networks to represent the space of odorants
Ngoc Tran, Daniel Kepple, Sergey Shuvaev et al.
Bayesian Generative Active Deep Learning
Toan Tran, Thanh-Toan Do, Ian Reid et al.
Discovering Latent Covariance Structures for Multiple Time Series
Anh Tong, Jaesik Choi
Optimal Transport for structured data with application on graphs
Vayer Titouan, Nicolas Courty, Romain Tavenard et al.
Transfer of Samples in Policy Search via Multiple Importance Sampling
Andrea Tirinzoni, Mattia Salvini, Marcello Restelli
Random Matrix Improved Covariance Estimation for a Large Class of Metrics
Malik Tiomoko, Romain Couillet, Florent Bouchard et al.
ELF OpenGo: an analysis and open reimplementation of AlphaZero
Yuandong Tian, Jerry Ma, Qucheng Gong et al.
Combating Label Noise in Deep Learning using Abstention
Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff Bilmes et al.
Concentration Inequalities for Conditional Value at Risk
Philip Thomas, Erik Learned-Miller
Action Robust Reinforcement Learning and Applications in Continuous Control
Chen Tessler, Yonathan Efroni, Shie Mannor
Kernel Normalized Cut: a Theoretical Revisit
Yoshikazu Terada, Michio Yamamoto