Papers
11,951 papers found
No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks
Shyamgopal Karthik, Ameya Prabhu, Puneet K. Dokania et al.
Noise against noise: stochastic label noise helps combat inherent label noise
Pengfei Chen, Guangyong Chen, Junjie Ye et al.
Noise or Signal: The Role of Image Backgrounds in Object Recognition
Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas et al.
No MCMC for me: Amortized sampling for fast and stable training of energy-based models
Will Sussman Grathwohl, Jacob Jin Kelly, Milad Hashemi et al.
Non-asymptotic Confidence Intervals of Off-policy Evaluation: Primal and Dual Bounds
Yihao Feng, Ziyang Tang, na zhang et al.
Nonseparable Symplectic Neural Networks
Shiying Xiong, Yunjin Tong, Xingzhe He et al.
not-MIWAE: Deep Generative Modelling with Missing not at Random Data
Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-end Learning and Control
Ioannis Exarchos, Marcus Aloysius Pereira, Ziyi Wang et al.
Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation
Yuki Ohnishi, Jean Honorio
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
Benjamin Eysenbach, Shreyas Chaudhari, Swapnil Asawa et al.
Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation
Justin Fu, Sergey Levine
On Data-Augmentation and Consistency-Based Semi-Supervised Learning
Atin Ghosh, Alexandre H. Thiery
On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections
Peizhao Li, Yifei Wang, Han Zhao et al.
One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks
Atish Agarwala, Abhimanyu Das, Brendan Juba et al.
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning
Ren Wang, Kaidi Xu, Sijia Liu et al.
On Graph Neural Networks versus Graph-Augmented MLPs
Lei Chen, Zhengdao Chen, Joan Bruna
On InstaHide, Phase Retrieval, and Sparse Matrix Factorization
Sitan Chen, Xiaoxiao Li, Zhao Song et al.
On Learning Universal Representations Across Languages
Xiangpeng Wei, Rongxiang Weng, Yue Hu et al.
Online Adversarial Purification based on Self-supervised Learning
Changhao Shi, Chester Holtz, Gal Mishne
On Position Embeddings in BERT
Benyou Wang, Lifeng Shang, Christina Lioma et al.
On Self-Supervised Image Representations for GAN Evaluation
Stanislav Morozov, Andrey Voynov, Artem Babenko
On Statistical Bias In Active Learning: How and When to Fix It
Sebastian Farquhar, Yarin Gal, Tom Rainforth
On the Bottleneck of Graph Neural Networks and its Practical Implications
Uri Alon, Eran Yahav
On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow
Youssef Mroueh, Truyen Nguyen
On the Critical Role of Conventions in Adaptive Human-AI Collaboration
Andy Shih, Arjun Sawhney, Jovana Kondic et al.