Papers
1,821 papers found
Confident Approximate Policy Iteration for Efficient Local Planning in $q^\pi$-realizable MDPs
Gellért Weisz, András György, Tadashi Kozuno et al.
Approximate Value Equivalence
Christopher Grimm, Andre Barreto, Satinder P. Singh
A Multilabel Classification Framework for Approximate Nearest Neighbor Search
Ville Hyvönen, Elias Jääsaari, Teemu Roos
Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent
Kruno Lehman, Alain Durmus, Umut Simsekli
SOAR: Improved Indexing for Approximate Nearest Neighbor Search
Philip Sun, David Simcha, Dave Dopson et al.
Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games
Hedi Hadiji, Sarah Sachs, Tim van Erven et al.
An Efficient and Robust Framework for Approximate Nearest Neighbor Search with Attribute Constraint
Mengzhao Wang, Lingwei Lv, Xiaoliang Xu et al.
Optimal Regret Is Achievable with Bounded Approximate Inference Error: An Enhanced Bayesian Upper Confidence Bound Framework
Ziyi Huang, Henry Lam, Amirhossein Meisami et al.
A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference
Emile van Krieken, Thiviyan Thanapalasingam, Jakub Tomczak et al.
Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures
Runa Eschenhagen, Alexander Immer, Richard Turner et al.
Computing Approximate $\ell_p$ Sensitivities
Swati Padmanabhan, David Woodruff, Richard Zhang
Multi-Step Generalized Policy Improvement by Leveraging Approximate Models
Lucas N. Alegre, Ana Bazzan, Ann Nowe et al.
Differentially Private Approximate Near Neighbor Counting in High Dimensions
Alexandr Andoni, Piotr Indyk, Sepideh Mahabadi et al.
Fair, Polylog-Approximate Low-Cost Hierarchical Clustering
Marina Knittel, Max Springer, John Dickerson et al.
Team-PSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning
Stephen McAleer, Gabriele Farina, Gaoyue Zhou et al.
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions
Jonathan Schmidt, Philipp Hennig, Jörg Nick et al.
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance
Mircea Petrache, Shubhendu Trivedi
Robust low-rank training via approximate orthonormal constraints
Dayana Savostianova, Emanuele Zangrando, Gianluca Ceruti et al.
Approximate Allocation Matching for Structural Causal Bandits with Unobserved Confounders
Lai Wei, Muhammad Qasim Elahi, Mahsa Ghasemi et al.
Faster approximate subgraph counts with privacy
Dung Nguyen, Mahantesh Halappanavar, Venkatesh Srinivasan et al.
Approximate inference of marginals using the IBIA framework
Shivani Bathla, Vinita Vasudevan
Reparameterization invariance in approximate Bayesian inference
Hrittik Roy, Marco Miani, Carl Henrik Ek et al.
Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm
Leo Zhou, Joao Basso, Song Mei