Spotlight Papers
1,421 papers found • Page 19 of 29
Conference
Adaptive Rational Activations to Boost Deep Reinforcement Learning
Quentin Delfosse, Patrick Schramowski, Martin Mundt et al.
Addressing Signal Delay in Deep Reinforcement Learning
Wei Wang, Dongqi Han, Xufang Luo et al.
A Distributional Analogue to the Successor Representation
Harley Wiltzer, Jesse Farebrother, Arthur Gretton et al.
Adversarial AutoMixup
Huafeng Qin, Xin Jin, Yun Jiang et al.
A General Framework for User-Guided Bayesian Optimization
Carl Hvarfner, Frank Hutter, Luigi Nardi
A Geometric Decomposition of Finite Games: Convergence vs. Recurrence under Exponential Weights
Davide Legacci, Panayotis Mertikopoulos, Bary Pradelski
Agnostic Sample Compression Schemes for Regression
Idan Attias, Steve Hanneke, Aryeh Kontorovich et al.
A Hierarchical Bayesian Model for Few-Shot Meta Learning
Minyoung Kim, Timothy Hospedales
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging
Shiqiang Wang, Mingyue Ji
Allocation Requires Prediction Only if Inequality Is Low
Ali Shirali, Rediet Abebe, Moritz Hardt
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents
Jake Grigsby, Jim Fan, Yuke Zhu
A Mutual Information Perspective on Federated Contrastive Learning
Christos Louizos, Matthias Reisser, Denis Korzhenkov
Analyzing Feed-Forward Blocks in Transformers through the Lens of Attention Maps
Goro Kobayashi, Tatsuki Kuribayashi, Sho Yokoi et al.
An Efficient Maximal Ancestral Graph Listing Algorithm
Tian-Zuo Wang, Wen-Bo Du, Zhi-Hua Zhou
An Image Is Worth 1000 Lies: Transferability of Adversarial Images across Prompts on Vision-Language Models
Haochen Luo, Jindong Gu, Fengyuan Liu et al.
AnyText: Multilingual Visual Text Generation and Editing
Yuxiang Tuo, Wangmeng Xiang, Jun-Yan He et al.
A path-norm toolkit for modern networks: consequences, promises and challenges
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti et al.
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs
Thien Le, Luana Ruiz, Stefanie Jegelka
A Subquadratic Time Algorithm for Robust Sparse Mean Estimation
Ankit Pensia
Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning
Pratik Patil, Daniel LeJeune
Asymptotics of feature learning in two-layer networks after one gradient-step
Hugo Cui, Luca Pesce, Yatin Dandi et al.
A Tensor Decomposition Perspective on Second-order RNNs
Maude Lizaire, Michael Rizvi-Martel, Marawan Gamal et al.
A Theoretical Analysis of Backdoor Poisoning Attacks in Convolutional Neural Networks
Boqi Li, Weiwei Liu
A Theory of Fault-Tolerant Learning
Changlong Wu, Yifan Wang, Ananth Grama
At Which Training Stage Does Code Data Help LLMs Reasoning?
ma yingwei, Yue Liu, Yue Yu et al.
Auto-Encoding Morph-Tokens for Multimodal LLM
Kaihang Pan, Siliang Tang, Juncheng Li et al.
Automating the Selection of Proxy Variables of Unmeasured Confounders
Feng Xie, Zhengming Chen, Shanshan Luo et al.
Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation
Thomas Kleine Buening, Aadirupa Saha, Christos Dimitrakakis et al.
BarLeRIa: An Efficient Tuning Framework for Referring Image Segmentation
Yaoming Wang, Li Jin, XIAOPENG ZHANG et al.
Batch and match: black-box variational inference with a score-based divergence
Diana Cai, Chirag Modi, Loucas Pillaud-Vivien et al.
BatteryML: An Open-source Platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng et al.
BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models
Haotian Sun, Yuchen Zhuang, Wei Wei et al.
BECLR: Batch Enhanced Contrastive Few-Shot Learning
Stylianos Poulakakis-Daktylidis, Hadi Jamali-Rad
Behavior Generation with Latent Actions
Seungjae Lee, Yibin Wang, Haritheja Etukuru et al.
Benchmarking Algorithms for Federated Domain Generalization
Ruqi Bai, Saurabh Bagchi, David Inouye
Bespoke Solvers for Generative Flow Models
Neta Shaul, Juan Perez, Ricky T. Q. Chen et al.
Best Arm Identification for Stochastic Rising Bandits
Marco Mussi, Alessandro Montenegro, Francesco Trovò et al.
Beyond Implicit Bias: The Insignificance of SGD Noise in Online Learning
Nikhil Vyas, Depen Morwani, Rosie Zhao et al.
Beyond Memorization: Violating Privacy via Inference with Large Language Models
Robin Staab, Mark Vero, Mislav Balunovic et al.
Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints
Chaoqi Wang, Yibo Jiang, Chenghao Yang et al.
Beyond the Norms: Detecting Prediction Errors in Regression Models
Andres Altieri, Marco Romanelli, Georg Pichler et al.
Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies
Xiangyu Liu, Chenghao Deng, Yanchao Sun et al.
Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis
Jie Hao, Xiaochuan Gong, Mingrui Liu
Blending Imitation and Reinforcement Learning for Robust Policy Improvement
Xuefeng Liu, Takuma Yoneda, Rick Stevens et al.
Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares
Liangzu Peng, Wotao Yin
Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments
Yang Yang, Wenhai Wang, Zhe Chen et al.
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation
Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel
Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning
Xiyu Wang, Baijiong Lin, Daochang Liu et al.
BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models
Qingqing Cao, Sewon Min, Yizhong Wang et al.
By Tying Embeddings You Are Assuming the Distributional Hypothesis
Bertolotti Francesco, Walter Cazzola