Papers
Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA
Jordan Awan, Ana Kenney, Matthew Reimherr et al.
BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning
Asa Cooper Stickland, Iain Murray
Better generalization with less data using robust gradient descent
Matthew Holland, Kazushi Ikeda
Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio
Kaito Fujii, Shinsaku Sakaue
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
Anna Choromanska, Benjamin Cowen, Sadhana Kumaravel et al.
Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior
Fadhel Ayed, Juho Lee, Francois Caron
Bias Also Matters: Bias Attribution for Deep Neural Network Explanation
Shengjie Wang, Tianyi Zhou, Jeff Bilmes
Bilinear Bandits with Low-rank Structure
Kwang-Sung Jun, Rebecca Willett, Stephen Wright et al.
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables
Friso Kingma, Pieter Abbeel, Jonathan Ho
Blended Conditonal Gradients
Gábor Braun, Sebastian Pokutta, Dan Tu et al.
Boosted Density Estimation Remastered
Zac Cranko, Richard Nock
Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy
Kareem Amin, Alex Kulesza, Andres Munoz et al.
Breaking Inter-Layer Co-Adaptation by Classifier Anonymization
Ikuro Sato, Kohta Ishikawa, Guoqing Liu et al.
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms
Ashok Makkuva, Pramod Viswanath, Sreeram Kannan et al.
Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities
Octavian Ganea, Sylvain Gelly, Gary Becigneul et al.
Bridging Theory and Algorithm for Domain Adaptation
Yuchen Zhang, Tianle Liu, Mingsheng Long et al.
CAB: Continuous Adaptive Blending for Policy Evaluation and Learning
Yi Su, Lequn Wang, Michele Santacatterina et al.
Calibrated Approximate Bayesian Inference
Hanwen Xing, Geoff Nicholls, Jeong Lee
Calibrated Model-Based Deep Reinforcement Learning
Ali Malik, Volodymyr Kuleshov, Jiaming Song et al.
CapsAndRuns: An Improved Method for Approximately Optimal Algorithm Configuration
Gellert Weisz, Andras Gyorgy, Csaba Szepesvari
Categorical Feature Compression via Submodular Optimization
Mohammadhossein Bateni, Lin Chen, Hossein Esfandiari et al.
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models
Biwei Huang, Kun Zhang, Mingming Gong et al.
Causal Identification under Markov Equivalence: Completeness Results
Amin Jaber, Jiji Zhang, Elias Bareinboim
Cautious Regret Minimization: Online Optimization with Long-Term Budget Constraints
Nikolaos Liakopoulos, Apostolos Destounis, Georgios Paschos et al.
Certified Adversarial Robustness via Randomized Smoothing
Jeremy Cohen, Elan Rosenfeld, Zico Kolter