Papers
QSFL: A Two-Level Uplink Communication Optimization Framework for Federated Learning
Liping Yi, Wang Gang, Liu Xiaoguang
Quant-BnB: A Scalable Branch-and-Bound Method for Optimal Decision Trees with Continuous Features
Rahul Mazumder, Xiang Meng, Haoyue Wang
Quantification and Analysis of Layer-wise and Pixel-wise Information Discarding
Haotian Ma, Hao Zhang, Fan Zhou et al.
Quantifying and Learning Linear Symmetry-Based Disentanglement
Loek Tonnaer, Luis Armando Perez Rey, Vlado Menkovski et al.
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra
Nadiia Chepurko, Kenneth Clarkson, Lior Horesh et al.
Query-Efficient and Scalable Black-Box Adversarial Attacks on Discrete Sequential Data via Bayesian Optimization
Deokjae Lee, Seungyong Moon, Junhyeok Lee et al.
Random Forest Density Estimation
Hongwei Wen, Hanyuan Hang
Random Gegenbauer Features for Scalable Kernel Methods
Insu Han, Amir Zandieh, Haim Avron
RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression
Yu Gong, Greg Mori, Fred Tung
Reachability Constrained Reinforcement Learning
Dongjie Yu, Haitong Ma, Shengbo Li et al.
RECAPP: Crafting a More Efficient Catalyst for Convex Optimization
Yair Carmon, Arun Jambulapati, Yujia Jin et al.
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series
Daniel Kramer, Philine L Bommer, Carlo Tombolini et al.
Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs
Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov
Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks
Litian Liang, Yaosheng Xu, Stephen Mcaleer et al.
Re-evaluating Word Mover’s Distance
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models
Tudor Manole, Nhat Ho
Region-Based Semantic Factorization in GANs
Jiapeng Zhu, Yujun Shen, Yinghao Xu et al.
Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation
Daniel Vial, Advait Parulekar, Sanjay Shakkottai et al.
Regret Minimization with Performative Feedback
Meena Jagadeesan, Tijana Zrnic, Celestine Mendler-Dünner
Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning
Shentao Yang, Yihao Feng, Shujian Zhang et al.
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency
Qi Cai, Zhuoran Yang, Zhaoran Wang
Reinforcement Learning with Action-Free Pre-Training from Videos
Younggyo Seo, Kimin Lee, Stephen L James et al.
Removing Batch Normalization Boosts Adversarial Training
Haotao Wang, Aston Zhang, Shuai Zheng et al.
Representation Topology Divergence: A Method for Comparing Neural Network Representations.
Serguei Barannikov, Ilya Trofimov, Nikita Balabin et al.
Residual-Based Sampling for Online Outlier-Robust PCA
Tianhao Zhu, Jie Shen