Papers
11,951 papers found
Online Hyperparameter Meta-Learning with Hypergradient Distillation
Hae Beom Lee, Hayeon Lee, JaeWoong Shin et al.
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs
Naman Agarwal, Syomantak Chaudhuri, Prateek Jain et al.
On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning
Marc Vischer, Robert Tjarko Lange, Henning Sprekeler
On Non-Random Missing Labels in Semi-Supervised Learning
Xinting Hu, Yulei Niu, Chunyan Miao et al.
On-Policy Model Errors in Reinforcement Learning
Lukas Froehlich, Maksym Lefarov, Melanie Zeilinger et al.
On Predicting Generalization using GANs
Yi Zhang, Arushi Gupta, Nikunj Saunshi et al.
On Redundancy and Diversity in Cell-based Neural Architecture Search
Xingchen Wan, Binxin Ru, Pedro M Esperança et al.
On Robust Prefix-Tuning for Text Classification
Zonghan Yang, Yang Liu
On the approximation properties of recurrent encoder-decoder architectures
Zhong Li, Haotian Jiang, Qianxiao Li
On the benefits of maximum likelihood estimation for Regression and Forecasting
Pranjal Awasthi, Abhimanyu Das, Rajat Sen et al.
On the Certified Robustness for Ensemble Models and Beyond
Zhuolin Yang, Linyi Li, Xiaojun Xu et al.
On the Connection between Local Attention and Dynamic Depth-wise Convolution
Qi Han, Zejia Fan, Qi Dai et al.
On the Convergence of Certified Robust Training with Interval Bound Propagation
Yihan Wang, Zhouxing Shi, Quanquan Gu et al.
On the Convergence of mSGD and AdaGrad for Stochastic Optimization
ruinan Jin, Yu Xing, Xingkang He
On the Convergence of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning
Che Wang, Shuhan Yuan, Kai Shao et al.
On the Existence of Universal Lottery Tickets
Rebekka Burkholz, Nilanjana Laha, Rajarshi Mukherjee et al.
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications
Ziqiao Wang, Yongyi Mao
On the Importance of Difficulty Calibration in Membership Inference Attacks
Lauren Watson, Chuan Guo, Graham Cormode et al.
On the Importance of Firth Bias Reduction in Few-Shot Classification
Saba Ghaffari, Ehsan Saleh, David Forsyth et al.
On the Learning and Learnability of Quasimetrics
Tongzhou Wang, Phillip Isola
On the Limitations of Multimodal VAEs
Imant Daunhawer, Thomas M. Sutter, Kieran Chin-Cheong et al.
On the Optimal Memorization Power of ReLU Neural Networks
Gal Vardi, Gilad Yehudai, Ohad Shamir
On the Pitfalls of Analyzing Individual Neurons in Language Models
Omer Antverg, Yonatan Belinkov
On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks
Maximilian Seitzer, Arash Tavakoli, Dimitrije Antic et al.
On the relation between statistical learning and perceptual distances
Alexander Hepburn, Valero Laparra, Raul Santos-Rodriguez et al.