Papers
11,955 papers found
AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation
David Berthelot, Rebecca Roelofs, Kihyuk Sohn et al.
A Damped Newton Method Achieves Global $\mathcal O \left(\frac{1}{k^2}\right)$ and Local Quadratic Convergence Rate
Slavomír Hanzely, Dmitry Kamzolov, Dmitry Pasechnyuk et al.
Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space
Yaohua Wang, Yaobin Zhang, Fangyi Zhang et al.
Adaptive Wavelet Transformer Network for 3D Shape Representation Learning
Hao Huang, Yi Fang
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning
Biwei Huang, Fan Feng, Chaochao Lu et al.
ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models
Louis Rouillard, Demian Wassermann
A Decision Support System to Predict Acute Fish Toxicity
Anders L Madsen, S. Jannicke Moe, Thomas Braunbeck et al.
A Deep Variational Approach to Clustering Survival Data
Laura Manduchi, Ričards Marcinkevičs, Michela C. Massi et al.
Adversarially Robust Conformal Prediction
Asaf Gendler, Tsui-Wei Weng, Luca Daniel et al.
Adversarial Retriever-Ranker for Dense Text Retrieval
Hang Zhang, Yeyun Gong, Yelong Shen et al.
Adversarial Robustness Through the Lens of Causality
Yonggang Zhang, Mingming Gong, Tongliang Liu et al.
Adversarial Support Alignment
Shangyuan Tong, Timur Garipov, Yang Zhang et al.
Adversarial Unlearning of Backdoors via Implicit Hypergradient
Yi Zeng, Si Chen, Won Park et al.
AEVA: Black-box Backdoor Detection Using Adversarial Extreme Value Analysis
Junfeng Guo, Ang Li, Cong Liu
A fast and accurate splitting method for optimal transport: analysis and implementation
Vien V. Mai, Jacob Lindbäck, Mikael Johansson
A Fine-Grained Analysis on Distribution Shift
Olivia Wiles, Sven Gowal, Florian Stimberg et al.
A Fine-Tuning Approach to Belief State Modeling
Samuel Sokota, Hengyuan Hu, David J Wu et al.
A First-Occupancy Representation for Reinforcement Learning
Ted Moskovitz, Spencer R Wilson, Maneesh Sahani
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms
Mathieu Dagréou, Pierre Ablin, Samuel Vaiter et al.
A General Analysis of Example-Selection for Stochastic Gradient Descent
Yucheng Lu, Si Yi Meng, Christopher De Sa
A generalization of the randomized singular value decomposition
Nicolas Boulle, Alex Townsend
A Generalized Weighted Optimization Method for Computational Learning and Inversion
Kui Ren, Yunan Yang, Björn Engquist
A global convergence theory for deep ReLU implicit networks via over-parameterization
Tianxiang Gao, Hailiang Liu, Jia Liu et al.
A Johnson-Lindenstrauss Framework for Randomly Initialized CNNs
Ido Nachum, Jan Hazla, Michael Gastpar et al.
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations
Jinyuan Jia, Binghui Wang, Xiaoyu Cao et al.