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Publication search results
found 548 matches
- 2024
- Diptarka Chakraborty, Sourav Chakraborty, Gunjan Kumar, Kuldeep S. Meel:
Equivalence Testing: The Power of Bounded Adaptivity. AISTATS 2024: 3592-3600 - Yang Cai, Haipeng Luo, Chen-Yu Wei, Weiqiang Zheng:
Near-Optimal Policy Optimization for Correlated Equilibrium in General-Sum Markov Games. AISTATS 2024: 3889-3897 - Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Yoshua Bengio:
Simulation-Free Schrödinger Bridges via Score and Flow Matching. AISTATS 2024: 1279-1287 - Yue Xing, Xiaofeng Lin, Qifan Song, Yi Xu, Belinda Zeng, Guang Cheng:
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. AISTATS 2024: 199-207 - Marco Pegoraro, Sanketh Vedula, Aviv Rosenberg, Irene Tallini, Emanuele Rodolà, Alex M. Bronstein:
Vector Quantile Regression on Manifolds. AISTATS 2024: 1999-2007 - Zhao Song, Junze Yin, Lichen Zhang, Ruizhe Zhang:
Fast Dynamic Sampling for Determinantal Point Processes. AISTATS 2024: 244-252 - Zhao Song, Junze Yin, Lichen Zhang:
Solving Attention Kernel Regression Problem via Pre-conditioner. AISTATS 2024: 208-216 - Kaiqi Zhao, Ming Zhao:
Self-Supervised Quantization-Aware Knowledge Distillation. AISTATS 2024: 4375-4383 - Zheng Zhao, Sebastian Mair, Thomas B. Schön, Jens Sjölund:
On Feynman-Kac training of partial Bayesian neural networks. AISTATS 2024: 3223-3231 - Charles Xu, Laney Goldman, Valentina Guo, Benjamin Hollander-Bodie, Maedee Trank-Greene, Ian Adelstein, Edward De Brouwer, Rex Ying, Smita Krishnaswamy, Michael Perlmutter:
BLIS-Net: Classifying and Analyzing Signals on Graphs. AISTATS 2024: 4537-4545 - Yu Yang, Eric Gan, Gintare Karolina Dziugaite, Baharan Mirzasoleiman:
Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias. AISTATS 2024: 2953-2961 - Chen Li, Yoshihiro Yamanishi:
TenGAN: Pure Transformer Encoders Make an Efficient Discrete GAN for De Novo Molecular Generation. AISTATS 2024: 361-369 - Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen:
Enhancing In-context Learning via Linear Probe Calibration. AISTATS 2024: 307-315 - Amirhesam Abedsoltan, Parthe Pandit, Luis Rademacher, Mikhail Belkin:
On the Nyström Approximation for Preconditioning in Kernel Machines. AISTATS 2024: 3718-3726 - Jacob D. Abernethy, Robert E. Schapire, Umar Syed:
Lexicographic Optimization: Algorithms and Stability. AISTATS 2024: 2503-2511 - Mahed Abroshan, Andrew Elliott, Mohammad Mahdi Khalili:
Imposing Fairness Constraints in Synthetic Data Generation. AISTATS 2024: 2269-2277 - Juliette Achddou, Nicolò Cesa-Bianchi, Pierre Laforgue:
Multitask Online Learning: Listen to the Neighborhood Buzz. AISTATS 2024: 1846-1854 - Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Xingchen Wan, Vu Nguyen, Harald Oberhauser, Michael A. Osborne:
Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach. AISTATS 2024: 496-504 - Masaki Adachi, Brady Planden, David A. Howey, Michael A. Osborne, Sebastian Orbell, Natalia Ares, Krikamol Muandet, Siu Lun Chau:
Looping in the Human: Collaborative and Explainable Bayesian Optimization. AISTATS 2024: 505-513 - Arman Adibi, Nicolò Dal Fabbro, Luca Schenato, Sanjeev R. Kulkarni, H. Vincent Poor, George J. Pappas, Hamed Hassani, Aritra Mitra:
Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling. AISTATS 2024: 2746-2754 - Anass Aghbalou, Anne Sabourin, François Portier:
Sharp error bounds for imbalanced classification: how many examples in the minority class? AISTATS 2024: 838-846 - Tamim El Ahmad, Luc Brogat-Motte, Pierre Laforgue, Florence d'Alché-Buc:
Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels. AISTATS 2024: 109-117 - Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin M. Stangl:
Agnostic Multi-Robust Learning using ERM. AISTATS 2024: 2242-2250 - Amirhossein Ahmadian, Yifan Ding, Gabriel Eilertsen, Fredrik Lindsten:
Unsupervised Novelty Detection in Pretrained Representation Space with Locally Adapted Likelihood Ratio. AISTATS 2024: 874-882 - Maheed H. Ahmed, Mahsa Ghasemi:
Privacy-Preserving Decentralized Actor-Critic for Cooperative Multi-Agent Reinforcement Learning. AISTATS 2024: 2755-2763 - Kartik Ahuja, Amin Mansouri, Yixin Wang:
Multi-Domain Causal Representation Learning via Weak Distributional Invariances. AISTATS 2024: 865-873 - Ahmet Alacaoglu, Stephen J. Wright:
Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints. AISTATS 2024: 4627-4635 - Mohammad Mahmudul Alam, Edward Raff, Stella Biderman, Tim Oates, James Holt:
Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection. AISTATS 2024: 4042-4050 - Shima Alizadeh, Aniruddha Bhargava, Karthick Gopalswamy, Lalit Jain, Branislav Kveton, Ge Liu:
Pessimistic Off-Policy Multi-Objective Optimization. AISTATS 2024: 2980-2988 - Youssef Allouah, Rachid Guerraoui, Lê-Nguyên Hoang, Oscar Villemaud:
Robust Sparse Voting. AISTATS 2024: 991-999
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