Papers
11,951 papers found
Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation
Vincent Mai, Kaustubh Mani, Liam Paull
Sample Efficient Stochastic Policy Extragradient Algorithm for Zero-Sum Markov Game
Ziyi Chen, Shaocong Ma, Yi Zhou
Sample Selection with Uncertainty of Losses for Learning with Noisy Labels
Xiaobo Xia, Tongliang Liu, Bo Han et al.
Sampling with Mirrored Stein Operators
Jiaxin Shi, Chang Liu, Lester Mackey
Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation
Ross M Clarke, Elre Talea Oldewage, José Miguel Hernández-Lobato
Scalable Sampling for Nonsymmetric Determinantal Point Processes
Insu Han, Mike Gartrell, Jennifer Gillenwater et al.
SCALE: Automatically Finding RFC Compliance Bugs in DNS Nameservers
Siva Kesava Reddy Kakarla, Ryan Beckett, Todd Millstein et al.
Scale Efficiently: Insights from Pretraining and Finetuning Transformers
Yi Tay, Mostafa Dehghani, Jinfeng Rao et al.
Scale Mixtures of Neural Network Gaussian Processes
Hyungi Lee, Eunggu Yun, Hongseok Yang et al.
Scaling Laws for Neural Machine Translation
Behrooz Ghorbani, Orhan Firat, Markus Freitag et al.
Scarf: Self-Supervised Contrastive Learning using Random Feature Corruption
Dara Bahri, Heinrich Jiang, Yi Tay et al.
Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs
Jason McEwen, Christopher Wallis, Augustine N. Mavor-Parker
Scene Transformer: A unified architecture for predicting future trajectories of multiple agents
Jiquan Ngiam, Vijay Vasudevan, Benjamin Caine et al.
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion
Tim Dockhorn, Arash Vahdat, Karsten Kreis
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
Chenlin Meng, Yutong He, Yang Song et al.
Selective Ensembles for Consistent Predictions
Emily Black, Klas Leino, Matt Fredrikson
Self-ensemble Adversarial Training for Improved Robustness
Hongjun Wang, Yisen Wang
Self-Joint Supervised Learning
Navid Kardan, Mubarak Shah, Mitch Hill
Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis
Siyi Tang, Jared Dunnmon, Khaled Kamal Saab et al.
Self-Supervised Inference in State-Space Models
David Ruhe, Patrick Forré
Self-supervised Learning is More Robust to Dataset Imbalance
Hong Liu, Jeff Z. HaoChen, Adrien Gaidon et al.
Self-Supervision Enhanced Feature Selection with Correlated Gates
Changhee Lee, Fergus Imrie, Mihaela van der Schaar
Semi-relaxed Gromov-Wasserstein divergence and applications on graphs
Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli et al.
Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods
Xueyuan She, Saurabh Dash, Saibal Mukhopadhyay
Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning
Seanie Lee, Hae Beom Lee, Juho Lee et al.