Papers
Constructing a provably adversarially-robust classifier from a high accuracy one
Grzegorz Gluch, Rüdiger Urbanke
Context Mover’s Distance & Barycenters: Optimal Transport of Contexts for Building Representations
Sidak Pal Singh, Andreas Hug, Aymeric Dieuleveut et al.
Contextual Combinatorial Volatile Multi-armed Bandit with Adaptive Discretization
Andi Nika, Sepehr Elahi, Cem Tekin
Contextual Constrained Learning for Dose-Finding Clinical Trials
Hyun-Suk Lee, Cong Shen, James Jordon et al.
Contextual Online False Discovery Rate Control
Shiyun Chen, Shiva Kasiviswanathan
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling
Mojmir Mutny, Michal Derezinski, Andreas Krause
Convergence Rates of Gradient Descent and MM Algorithms for Bradley-Terry Models
Milan Vojnovic, Se-Young Yun, Kaifang Zhou
Convergence Rates of Smooth Message Passing with Rounding in Entropy-Regularized MAP Inference
Jonathan Lee, Aldo Pacchiano, Michael Jordan
Convex Geometry of Two-Layer ReLU Networks: Implicit Autoencoding and Interpretable Models
Tolga Ergen, Mert Pilanci
Coping With Simulators That Don’t Always Return
Andrew Warrington, Saeid Naderiparizi, Frank Wood
Corruption-Tolerant Gaussian Process Bandit Optimization
Ilija Bogunovic, Andreas Krause, Jonathan Scarlett
Data Generation for Neural Programming by Example
Judith Clymo, Haik Manukian, Nathanael Fijalkow et al.
DAve-QN: A Distributed Averaged Quasi-Newton Method with Local Superlinear Convergence Rate
Saeed Soori, Konstantin Mishchenko, Aryan Mokhtari et al.
Decentralized gradient methods: does topology matter?
Giovanni Neglia, Chuan Xu, Don Towsley et al.
Decentralized Multi-player Multi-armed Bandits with No Collision Information
Chengshuai Shi, Wei Xiong, Cong Shen et al.
Deep Active Learning: Unified and Principled Method for Query and Training
Changjian Shui, Fan Zhou, Christian Gagné et al.
Deep Structured Mixtures of Gaussian Processes
Martin Trapp, Robert Peharz, Franz Pernkopf et al.
Deontological Ethics By Monotonicity Shape Constraints
Serena Wang, Maya Gupta
Dependent randomized rounding for clustering and partition systems with knapsack constraints
David Harris, Thomas Pensyl, Aravind Srinivasan et al.
Derivative-Free & Order-Robust Optimisation
Haitham Ammar, Victor Gabillon, Rasul Tutunov et al.
Deterministic Decoding for Discrete Data in Variational Autoencoders
Daniil Polykovskiy, Dmitry Vetrov
Diameter-based Interactive Structure Discovery
Christopher Tosh, Daniel Hsu
Differentiable Causal Backdoor Discovery
Limor Gultchin, Matt Kusner, Varun Kanade et al.
Differentiable Feature Selection by Discrete Relaxation
Rishit Sheth, Nicoló Fusi
Discrete Action On-Policy Learning with Action-Value Critic
Yuguang Yue, Yunhao Tang, Mingzhang Yin et al.