Papers
Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data
Deepesh Data, Suhas Diggavi
Calibrate Before Use: Improving Few-shot Performance of Language Models
Zihao Zhao, Eric Wallace, Shi Feng et al.
Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang, Kartik Ahuja, Yilun Xu et al.
CARTL: Cooperative Adversarially-Robust Transfer Learning
Dian Chen, Hongxin Hu, Qian Wang et al.
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization
Stanislaw Jastrzebski, Devansh Arpit, Oliver Astrand et al.
CATE: Computation-aware Neural Architecture Encoding with Transformers
Shen Yan, Kaiqiang Song, Fei Liu et al.
Catformer: Designing Stable Transformers via Sensitivity Analysis
Jared Q Davis, Albert Gu, Krzysztof Choromanski et al.
Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning
Sumedh A Sontakke, Arash Mehrjou, Laurent Itti et al.
ChaCha for Online AutoML
Qingyun Wu, Chi Wang, John Langford et al.
Characterizing Fairness Over the Set of Good Models Under Selective Labels
Amanda Coston, Ashesh Rambachan, Alexandra Chouldechova
Characterizing Structural Regularities of Labeled Data in Overparameterized Models
Ziheng Jiang, Chiyuan Zhang, Kunal Talwar et al.
Characterizing the Gap Between Actor-Critic and Policy Gradient
Junfeng Wen, Saurabh Kumar, Ramki Gummadi et al.
Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication
Sangwoo Hong, Heecheol Yang, Youngseok Yoon et al.
CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
Hanshu Yan, Jingfeng Zhang, Gang Niu et al.
Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels
Songhua Wu, Xiaobo Xia, Tongliang Liu et al.
Classification with Rejection Based on Cost-sensitive Classification
Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang et al.
Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed
Maria Refinetti, Sebastian Goldt, Florent Krzakala et al.
CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients
Dani Kiyasseh, Tingting Zhu, David A Clifton
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels
Zhaowei Zhu, Yiwen Song, Yang Liu
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
Yann Fraboni, Richard Vidal, Laetitia Kameni et al.
Coach-Player Multi-agent Reinforcement Learning for Dynamic Team Composition
Bo Liu, Qiang Liu, Peter Stone et al.
Coded-InvNet for Resilient Prediction Serving Systems
Tuan Dinh, Kangwook Lee
Collaborative Bayesian Optimization with Fair Regret
Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low et al.
Combinatorial Blocking Bandits with Stochastic Delays
Alexia Atsidakou, Orestis Papadigenopoulos, Soumya Basu et al.