Papers
High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds
Noémie Jaquier, Leonel Rozo
The Cone of Silence: Speech Separation by Localization
Teerapat Jenrungrot, Vivek Jayaram, Steve Seitz et al.
A Self-Tuning Actor-Critic Algorithm
Tom Zahavy, Zhongwen Xu, Vivek Veeriah et al.
Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction
David Novotny, Roman Shapovalov, Andrea Vedaldi
Linearly Converging Error Compensated SGD
Eduard Gorbunov, Dmitry Kovalev, Dmitry Makarenko et al.
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems
Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi et al.
Gradient-EM Bayesian Meta-Learning
Yayi Zou, Xiaoqi Lu
The Generalization-Stability Tradeoff In Neural Network Pruning
Brian Bartoldson, Ari Morcos, Adrian Barbu et al.
Adversarial Attacks on Deep Graph Matching
Zijie Zhang, Zeru Zhang, Yang Zhou et al.
Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher
Guangda Ji, Zhanxing Zhu
Probabilistic Active Meta-Learning
Jean Kaddour, Steindor Saemundsson, Marc Deisenroth (he/him)
Statistical and Topological Properties of Sliced Probability Divergences
Kimia Nadjahi, Alain Durmus, Lénaïc Chizat et al.
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability
Nathan Inkawhich, Kevin Liang, Binghui Wang et al.
Curvature Regularization to Prevent Distortion in Graph Embedding
Hongbin Pei, Bingzhe Wei, Kevin Chang et al.
Tight last-iterate convergence rates for no-regret learning in multi-player games
Noah Golowich, Sarath Pattathil, Constantinos Daskalakis
Meta-Learning with Adaptive Hyperparameters
Sungyong Baik, Myungsub Choi, Janghoon Choi et al.
Top-KAST: Top-K Always Sparse Training
Siddhant Jayakumar, Razvan Pascanu, Jack Rae et al.
Meta-Learning through Hebbian Plasticity in Random Networks
Elias Najarro, Sebastian Risi
Finding All ε-Good Arms in Stochastic Bandits
Blake Mason, Lalit Jain, Ardhendu Tripathy et al.
Deep Diffusion-Invariant Wasserstein Distributional Classification
Sung Woo Park, Dong Wook Shu, Junseok Kwon
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
Zhisheng Xiao, Qing Yan, Yali Amit
Learning from Failure: De-biasing Classifier from Biased Classifier
Junhyun Nam, Hyuntak Cha, Sungsoo Ahn et al.
Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language Navigation
Zhiwei Deng, Karthik Narasimhan, Olga Russakovsky
IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method
Yossi Arjevani, Joan Bruna, Bugra Can et al.