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Publication search results
found 1,346 matches
- 2024
- Gavin Brown, Riccardo Ali:
Bias/Variance is not the same as Approximation/Estimation. Trans. Mach. Learn. Res. 2024 (2024) - Albert Ziegler, Pawel Czyz:
Bayesian Quantification with Black-Box Estimators. Trans. Mach. Learn. Res. 2024 (2024) - Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio:
Improving and generalizing flow-based generative models with minibatch optimal transport. Trans. Mach. Learn. Res. 2024 (2024) - Sebastian Mair, Jens Sjölund:
Archetypal Analysis++: Rethinking the Initialization Strategy. Trans. Mach. Learn. Res. 2024 (2024) - Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister:
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. Trans. Mach. Learn. Res. 2024 (2024) - Zhuosheng Zhang, Aston Zhang, Mu Li, Hai Zhao, George Karypis, Alex Smola:
Multimodal Chain-of-Thought Reasoning in Language Models. Trans. Mach. Learn. Res. 2024 (2024) - Peiran Xu, Zeyu Wang, Jieru Mei, Liangqiong Qu, Alan L. Yuille, Cihang Xie, Yuyin Zhou:
FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning. Trans. Mach. Learn. Res. 2024 (2024) - Daniel Waxman, Petar M. Djuric:
Dynamic Online Ensembles of Basis Expansions. Trans. Mach. Learn. Res. 2024 (2024) - Yue Kang, Cho-Jui Hsieh, Thomas C. M. Lee:
Online Continuous Hyperparameter Optimization for Generalized Linear Contextual Bandits. Trans. Mach. Learn. Res. 2024 (2024) - Jonathan Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill:
Estimating Optimal Policy Value in Linear Contextual Bandits Beyond Gaussianity. Trans. Mach. Learn. Res. 2024 (2024) - Zheyuan Liu, Weixuan Sun, Damien Teney, Stephen Gould:
Candidate Set Re-ranking for Composed Image Retrieval with Dual Multi-modal Encoder. Trans. Mach. Learn. Res. 2024 (2024) - Fang Kong, Xiangcheng Zhang, Baoxiang Wang, Shuai Li:
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization. Trans. Mach. Learn. Res. 2024 (2024) - Wei Duan, Jie Lu, Yu Guang Wang, Junyu Xuan:
Layer-diverse Negative Sampling for Graph Neural Networks. Trans. Mach. Learn. Res. 2024 (2024) - Haoxiang Wang, Haozhe Si, Huajie Shao, Han Zhao:
Enhancing Compositional Generalization via Compositional Feature Alignment. Trans. Mach. Learn. Res. 2024 (2024) - Qitong Wang, Georgios Kollias, Vasileios Kalantzis, Naoki Abe, Mohammed J. Zaki:
Directed Graph Transformers. Trans. Mach. Learn. Res. 2024 (2024) - Haoxiang Wang, Zhanhong Jiang, Chao Liu, Soumik Sarkar, Dongxiang Jiang, Young M. Lee:
Asynchronous Training Schemes in Distributed Learning with Time Delay. Trans. Mach. Learn. Res. 2024 (2024) - Tong Wu:
Online Tensor Max-Norm Regularization via Stochastic Optimization. Trans. Mach. Learn. Res. 2024 (2024) - Yi Shen, Pan Xu, Michael M. Zavlanos:
Wasserstein Distributionally Robust Policy Evaluation and Learning for Contextual Bandits. Trans. Mach. Learn. Res. 2024 (2024) - Meng Liu, Haiyang Yu, Shuiwang Ji:
Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm. Trans. Mach. Learn. Res. 2024 (2024) - Han Wang, Aritra Mitra, Hamed Hassani, George J. Pappas, James Anderson:
Federated TD Learning with Linear Function Approximation under Environmental Heterogeneity. Trans. Mach. Learn. Res. 2024 (2024) - Yuan Liu, Songyang Zhang, Jiacheng Chen, Kai Chen, Dahua Lin:
PixMIM: Rethinking Pixel Reconstruction in Masked Image Modeling. Trans. Mach. Learn. Res. 2024 (2024) - Xiao Li, Sheng Liu, Jinxin Zhou, Xinyu Lu, Carlos Fernandez-Granda, Zhihui Zhu, Qing Qu:
Understanding and Improving Transfer Learning of Deep Models via Neural Collapse. Trans. Mach. Learn. Res. 2024 (2024) - Yue Wang, Jinjun Xiong, Shaofeng Zou:
Achieving the Asymptotically Minimax Optimal Sample Complexity of Offline Reinforcement Learning: A DRO-Based Approach. Trans. Mach. Learn. Res. 2024 (2024) - Jing Wang, Wonho Bae, Jiahong Chen, Kuangen Zhang, Leonid Sigal, Clarence W. de Silva:
What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context. Trans. Mach. Learn. Res. 2024 (2024) - Bo Li, Yasin Esfandiari, Mikkel N. Schmidt, Tommy Sonne Alstrøm, Sebastian U. Stich:
Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity. Trans. Mach. Learn. Res. 2024 (2024) - Vincent Abbott:
Neural Circuit Diagrams: Robust Diagrams for the Communication, Implementation, and Analysis of Deep Learning Architectures. Trans. Mach. Learn. Res. 2024 (2024) - Taiga Abe, Estefany Kelly Buchanan, Geoff Pleiss, John P. Cunningham:
Pathologies of Predictive Diversity in Deep Ensembles. Trans. Mach. Learn. Res. 2024 (2024) - Germán Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Pablo Polosecki, Irina Rish, Silvina Ponce Dawson, Guillermo A. Cecchi, Guillaume Dumas:
Effective Latent Differential Equation Models via Attention and Multiple Shooting. Trans. Mach. Learn. Res. 2024 (2024) - Futoon M. Abushaqra, Hao Xue, Yongli Ren, Flora D. Salim:
SeqLink: A Robust Neural-ODE Architecture for Modelling Partially Observed Time Series. Trans. Mach. Learn. Res. 2024 (2024) - Juliette Achddou, Olivier Cappé, Aurélien Garivier:
Stochastic Direct Search Methods for Blind Resource Allocation. Trans. Mach. Learn. Res. 2024 (2024)
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