2024 Papers
12,324 papers found • Page 3 of 247
964 Measuring Self-Supervised Representation Quality for Downstream Classification Using Discriminative Features
Neha Kalibhat, Kanika Narang, Hamed Firooz et al.
A 2-Dimensional State Space Layer for Spatial Inductive Bias
Ethan Baron, Itamar Zimerman, Lior Wolf
A2Q+: Improving Accumulator-Aware Weight Quantization
Ian Colbert, Alessandro Pappalardo, Jakoba Petri-Koenig et al.
A2XP: Towards Private Domain Generalization
Geunhyeok Yu, Hyoseok Hwang
A3S: A General Active Clustering Method with Pairwise Constraints
Xun Deng, Junlong Liu, Han Zhong et al.
AACP: Aesthetics Assessment of Children’s Paintings Based on Self
Supervised Learning
AAMDM: Accelerated Auto-regressive Motion Diffusion Model
Tianyu Li, Calvin Zhuhan Qiao, Ren Guanqiao et al.
A Backpack Full of Skills: Egocentric Video Understanding with Diverse Task Perspectives
Simone Alberto Peirone, Francesca Pistilli, Antonio Alliegro et al.
A Bayesian Approach to Online Planning
Nir Greshler, David Ben Eli, Carmel Rabinovitz et al.
A Bayesian Approach to OOD Robustness in Image Classification
Prakhar Kaushik, Adam Kortylewski, Alan L. Yuille
A&B BNN: Add&Bit-Operation-Only Hardware-Friendly Binary Neural Network
Ruichen Ma, Guanchao Qiao, Yian Liu et al.
ABC Easy as 123: A Blind Counter for Exemplar-Free Multi-Class Class-agnostic Counting
Michael A Hobley, Victor Adrian Prisacariu
Abductive Ego-View Accident Video Understanding for Safe Driving Perception
Jianwu Fang, Lei-lei Li, Junfei Zhou et al.
A Benchmark for Learning to Translate a New Language from One Grammar Book
Garrett Tanzer, Mirac Suzgun, Eline Visser et al.
A Benchmark Study on Calibration
Linwei Tao, Younan Zhu, Haolan Guo et al.
A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models
Sebastian Gregor Gruber, Florian Buettner
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
Haozhe Jiang, Qiwen Cui, Zhihan Xiong et al.
A Brain-Inspired Way of Reducing the Network Complexity via Concept-Regularized Coding for Emotion Recognition
Han Lu, Xiahai Zhuang, Qiang Luo
A Branching Decoder for Set Generation
Zixian Huang, Gengyang Xiao, Yu Gu et al.
A Bregman Proximal Stochastic Gradient Method with Extrapolation for Nonconvex Nonsmooth Problems
Qingsong Wang, Zehui Liu, Chunfeng Cui et al.
Absolute Policy Optimization: Enhancing Lower Probability Bound of Performance with High Confidence
Weiye Zhao, Feihan Li, Yifan Sun et al.
Absolute Pose from One or Two Scaled and Oriented Features
Jonathan Ventura, Zuzana Kukelova, Torsten Sattler et al.
Abstract Action Scheduling for Optimal Temporal Planning via OMT
Stefan Panjkovic, Andrea Micheli
Abstract and Explore: A Novel Behavioral Metric with Cyclic Dynamics in Reinforcement Learning
Anjie Zhu, Peng-Fei Zhang, Ruihong Qiu et al.
Abstraction of Situation Calculus Concurrent Game Structures
Yves Lesperance, Giuseppe De Giacomo, Maryam Rostamigiv et al.
Abstractors and relational cross-attention: An inductive bias for explicit relational reasoning in Transformers
Awni Altabaa, Taylor Webb, Jonathan Cohen et al.
A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
Jakub Paplham, Vojtech Franc
ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation
Yuewen Sun, Erli Wang, Biwei Huang et al.
A Category Agnostic Model for Visual Rearrangment
Yuyi Liu, Xinhang Song, Weijie Li et al.
AccDiffusion: An Accurate Method for Higher-Resolution Image Generation
Zhihang Lin, Mingbao Lin, Meng Zhao et al.
Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion
Yang Cai, Argyris Oikonomou, Weiqiang Zheng
Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise
Rui Pan, Yuxing Liu, Xiaoyu Wang et al.
Accelerated Policy Gradient for s-rectangular Robust MDPs with Large State Spaces
Ziyi Chen, Heng Huang
Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning
Yen-Ju Chen, Nai-Chieh Huang, Ching-pei Lee et al.
Accelerated Sampling with Stacked Restricted Boltzmann Machines
Jorge Fernandez-de-Cossio-Diaz, Clément Roussel, Simona Cocco et al.
Accelerated Speculative Sampling Based on Tree Monte Carlo
Zhengmian Hu, Heng Huang
Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning
Jiayu Chen, Zelai Xu, Yunfei Li et al.
Accelerating Convergence in Bayesian Few-Shot Classification
Tianjun Ke, Haoqun Cao, Feng Zhou
Accelerating Convergence of Score-Based Diffusion Models, Provably
Gen Li, Yu Huang, Timofey Efimov et al.
Accelerating Cutting-Plane Algorithms via Reinforcement Learning Surrogates
12620 Kyle Mana, Fernando Acero, Stephen Mak et al.
Accelerating Data Generation for Neural Operators via Krylov Subspace Recycling
Hong Wang, Zhongkai Hao, Jie Wang et al.
Accelerating Diffusion Sampling with Optimized Time Steps
Shuchen Xue, Zhaoqiang Liu, Fei Chen et al.
Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks
Jie Hu, Vishwaraj Doshi, Do Young Eun
Accelerating Federated Learning with Quick Distributed Mean Estimation
Ran Ben Basat, Shay Vargaftik, Amit Portnoy et al.
Accelerating Heterogeneous Federated Learning with Closed-form Classifiers
Eros Fanì, Raffaello Camoriano, Barbara Caputo et al.
Accelerating Image Generation with Sub-path Linear Approximation Model
Chen Xu, Tianhui Song, Weixin Feng et al.
Accelerating Image Super-Resolution Networks with Pixel-Level Classification
Jinho Jeong, Jinwoo Kim, Younghyun Jo et al.
Accelerating Iterative Retrieval-augmented Language Model Serving with Speculation
Zhihao Zhang, Alan Zhu, Lijie Yang et al.
Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving
Sohei Arisaka, Qianxiao Li
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need
Shangda Yang, Vitaly Zankin, Maximilian Balandat et al.