Most Cited 2024 "3d hand estimation" Papers
12,324 papers found • Page 60 of 62
Conference
Purifying Quantization-conditioned Backdoors via Layer-wise Activation Correction with Distribution Approximation
Boheng Li, Yishuo Cai, Jisong Cai et al.
Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition
Yuke Li, Guangyi Chen, Ben Abramowitz et al.
Data Poisoning Attacks against Conformal Prediction
Yangyi Li, Aobo Chen, Wei Qian et al.
Positive and Unlabeled Learning with Controlled Probability Boundary Fence
Changchun Li, Yuanchao Dai, Lei Feng et al.
Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection
yuxin li, Yaoxuan Feng, Bo Chen et al.
Value-Evolutionary-Based Reinforcement Learning
Pengyi Li, Jianye Hao, Hongyao Tang et al.
Image Clustering with External Guidance
Yunfan Li, Peng Hu, Dezhong Peng et al.
VisionGraph: Leveraging Large Multimodal Models for Graph Theory Problems in Visual Context
yunxin li, Baotian Hu, Haoyuan Shi et al.
Accelerating Convergence of Score-Based Diffusion Models, Provably
Gen Li, Yu Huang, Timofey Efimov et al.
Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions
Weihan Li, Chengrui Li, Yule Wang et al.
Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
Baohong Li, Haoxuan Li, Ruoxuan Xiong et al.
Configurable Mirror Descent: Towards a Unification of Decision Making
Pengdeng Li, Shuxin Li, Chang Yang et al.
A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data
Wenqiang Li, Weijun Li, Lina Yu et al.
Preventing Model Collapse in Gaussian Process Latent Variable Models
Ying Li, Zhidi Lin, Feng Yin et al.
Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once
Zhangheng Li, Shiwei Liu, Tianlong Chen et al.
Learning Adaptive and View-Invariant Vision Transformer for Real-Time UAV Tracking
Yongxin Li, Mengyuan Liu, You Wu et al.
PID: Prompt-Independent Data Protection Against Latent Diffusion Models
Ang Li, Yichuan Mo, Mingjie Li et al.
Privacy Preserving Adaptive Experiment Design
Jiachun Li, Kaining Shi, David Simchi-Levi
LoRAP: Transformer Sub-Layers Deserve Differentiated Structured Compression for Large Language Models
guangyan li, Yongqiang Tang, Wensheng Zhang
Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning
Depeng Li, Tianqi Wang, Junwei Chen et al.
VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling
Siyuan Li, Zedong Wang, Zicheng Liu et al.
OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift
Lin Li, Yifei Wang, Chawin Sitawarin et al.
$\bf{\Phi}_\textrm{Flow}$: Differentiable Simulations for PyTorch, TensorFlow and Jax
Philipp Holl, Nils Thuerey
Two-Stage Shadow Inclusion Estimation: An IV Approach for Causal Inference under Latent Confounding and Collider Bias
Baohong Li, Anpeng Wu, Ruoxuan Xiong et al.
FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction
Zhonghang Li, Lianghao Xia, Yong Xu et al.
Towards efficient deep spiking neural networks construction with spiking activity based pruning
Yaxin Li, Qi Xu, Jiangrong Shen et al.
FedBAT: Communication-Efficient Federated Learning via Learnable Binarization
Shiwei Li, Wenchao Xu, Haozhao Wang et al.
Beyond Point Prediction: Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process
Zichong Li, Qunzhi Xu, Zhenghao Xu et al.
Statistical Properties of Robust Satisficing
zhiyi li, Yunbei Xu, Ruohan Zhan
KernelWarehouse: Rethinking the Design of Dynamic Convolution
Chao Li, Anbang Yao
GeoReasoner: Geo-localization with Reasoning in Street Views using a Large Vision-Language Model
Ling Li, Yu Ye, Bingchuan Jiang et al.
Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis
Yingying Li, Jing Yu, Lauren Conger et al.
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks
Haoyu Li, Shichang Zhang, Longwen Tang et al.
EvoRainbow: Combining Improvements in Evolutionary Reinforcement Learning for Policy Search
Pengyi Li, Yan Zheng, Hongyao Tang et al.
Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset
Shijie Lian, Ziyi Zhang, Hua Li et al.
On the Error-Propagation of Inexact Hotelling's Deflation for Principal Component Analysis
Fangshuo Liao, J. Lyle Kim, Cruz Barnum et al.
Bootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium
Luofeng Liao, Christian Kroer
An Effective Dynamic Gradient Calibration Method for Continual Learning
Weichen Lin, Jiaxiang Chen, Ruomin Huang et al.
Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data
Kang Lin, Reinhard Heckel
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
Yuchao Lin, Jacob Helwig, Shurui Gui et al.
HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network
Bor Jiun Lin, Chun-Yi Lee
Parsimonious Learning-Augmented Approximations for Dense Instances of $\mathcal{NP}$-hard Problems
Evripidis Bampis, Bruno Escoffier, Michalis Xefteris
On Hypothesis Transfer Learning of Functional Linear Models
Haotian Lin, Matthew Reimherr
A Single-Loop Robust Policy Gradient Method for Robust Markov Decision Processes
Zhenwei Lin, Chenyu Xue, Qi Deng et al.
Autonomous Sparse Mean-CVaR Portfolio Optimization
Yizun Lin, Yangyu Zhang, Zhao-Rong Lai et al.
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
Hossein Zakerinia, Amin Behjati, Christoph Lampert
PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching
Haitao Lin, Odin Zhang, Huifeng Zhao et al.
Position: A Call to Action for a Human-Centered AutoML Paradigm
Marius Lindauer, Florian Karl, Anne Klier et al.
Graph Distillation with Eigenbasis Matching
Yang Liu, Deyu Bo, Chuan Shi
Adaptive Text Watermark for Large Language Models
Yepeng Liu, Yuheng Bu
Graph Adversarial Diffusion Convolution
Songtao Liu, Jinghui Chen, Tianfan Fu et al.
ESNet: Evolution and Succession Network for High-Resolution Salient Object Detection
Hongyu Liu, Runmin Cong, Hua Li et al.
Unifying Image Processing as Visual Prompting Question Answering
Yihao Liu, Xiangyu Chen, Xianzheng Ma et al.
The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks
Ziquan Liu, Yufei Cui, Yan Yan et al.
Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models
Songtao Liu, Hanjun Dai, Yue Zhao et al.
Decoding-time Realignment of Language Models
Tianlin Liu, Shangmin Guo, Leonardo Martins Bianco et al.
DIDI: Diffusion-Guided Diversity for Offline Behavioral Generation
Jinxin Liu, Xinghong Guo, Zifeng Zhuang et al.
On the Feasibility of Single-Pass Full-Capacity Learning in Linear Threshold Neurons with Binary Input Vectors
Ruipeng Liu, Borui He, Naveed Tahir et al.
Online Speculative Decoding
Xiaoxuan Liu, Lanxiang Hu, Peter Bailis et al.
Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy
Yi Liu, Qirui Hu, Linglong Kong
Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion
Xuantong Liu, Tianyang Hu, Wenjia Wang et al.
Reason for Future, Act for Now: A Principled Architecture for Autonomous LLM Agents
Zhihan Liu, Hao Hu, Shenao Zhang et al.
Convergence of Online Learning Algorithm for a Mixture of Multiple Linear Regressions
Yujing Liu, Zhixin Liu, Lei Guo
Energy-Guided Diffusion Sampling for Offline-to-Online Reinforcement Learning
Xu-Hui Liu, Tian-Shuo Liu, Shengyi Jiang et al.
Moreau Envelope for Nonconvex Bi-Level Optimization: A Single-Loop and Hessian-Free Solution Strategy
Risheng Liu, Zhu Liu, Wei Yao et al.
Floating Anchor Diffusion Model for Multi-motif Scaffolding
Ke Liu, Weian Mao, Shuaike Shen et al.
Federated Representation Learning in the Under-Parameterized Regime
Renpu Liu, Cong Shen, Jing Yang
Causal Discovery via Conditional Independence Testing with Proxy Variables
Mingzhou Liu, Xinwei Sun, YU QIAO et al.
Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement
che liu, Zhongwei Wan, Cheng Ouyang et al.
High-Probability Bound for Non-Smooth Non-Convex Stochastic Optimization with Heavy Tails
Langqi Liu, Yibo Wang, Lijun Zhang
Language-Driven Cross-Modal Classifier for Zero-Shot Multi-Label Image Recognition
Yicheng Liu, Jie Wen, Chengliang Liu et al.
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
Jiashuo Liu, Jiayun Wu, Tianyu Wang et al.
Timer: Generative Pre-trained Transformers Are Large Time Series Models
Yong Liu, Haoran Zhang, Chenyu Li et al.
On the Last-Iterate Convergence of Shuffling Gradient Methods
Zijian Liu, Zhengyuan Zhou
Neural Operators with Localized Integral and Differential Kernels
Miguel Liu-Schiaffini, Julius Berner, Boris Bonev et al.
A Tensor Decomposition Perspective on Second-order RNNs
Maude Lizaire, Michael Rizvi-Martel, Marawan Gamal et al.
Reparameterized Importance Sampling for Robust Variational Bayesian Neural Networks
Yunfei Long, Zilin Tian, Liguo Zhang et al.
Attention Meets Post-hoc Interpretability: A Mathematical Perspective
Gianluigi Lopardo, Frederic Precioso, Damien Garreau
Non-Vacuous Generalization Bounds for Large Language Models
Sanae Lotfi, Marc Finzi, Yilun Kuang et al.
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
Aaron Lou, Chenlin Meng, Stefano Ermon
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization
Andrew Lowy, Jonathan Ullman, Stephen Wright
Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models
Zhihe Lu, Jiawang Bai, Xin Li et al.
Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training
Lin Lu, Chenxi Dai, Wangcheng Tao et al.
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
Xing Han Lù, Zdeněk Kasner, Siva Reddy
CauDiTS: Causal Disentangled Domain Adaptation of Multivariate Time Series
Junxin Lu, Shiliang Sun
FiT: Flexible Vision Transformer for Diffusion Model
Zeyu Lu, ZiDong Wang, Di Huang et al.
SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
Xudong LU, Aojun Zhou, Yuhui Xu et al.
Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression
Zhankun Luo, Abolfazl Hashemi
OMPO: A Unified Framework for RL under Policy and Dynamics Shifts
Yu Luo, Tianying Ji, Fuchun Sun et al.
Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL
Yu Luo, Tianying Ji, Fuchun Sun et al.
Potential Based Diffusion Motion Planning
Yunhao Luo, Chen Sun, Josh Tenenbaum et al.
Cluster-Aware Similarity Diffusion for Instance Retrieval
Jifei Luo, Hantao Yao, Changsheng Xu
Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models
Qitan Lv, Jie Wang, Hanzhu Chen et al.
Efficient and Effective Time-Series Forecasting with Spiking Neural Networks
Changze Lv, Yansen Wang, Dongqi Han et al.
Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
Xinyu Ma, Xu Chu, Zhibang Yang et al.
Outlier-aware Slicing for Post-Training Quantization in Vision Transformer
Yuexiao Ma, Huixia Li, Xiawu Zheng et al.
X-Oscar: A Progressive Framework for High-quality Text-guided 3D Animatable Avatar Generation
Yiwei Ma, Zhekai Lin, Jiayi Ji et al.
SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment
Ziping Ma, Furong Xu, Jian liu et al.
A Provable Decision Rule for Out-of-Distribution Detection
Xinsong Ma, Xin Zou, Weiwei Liu
On the Hardness of Probabilistic Neurosymbolic Learning
Jaron Maene, Vincent Derkinderen, Luc De Raedt
LASER: Linear Compression in Wireless Distributed Optimization
Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels et al.
Entropy-Reinforced Planning with Large Language Models for Drug Discovery
Xuefeng Liu, Chih-chan Tien, Peng Ding et al.
Auto-Regressive Next-Token Predictors are Universal Learners
Eran Malach
Tilting the Odds at the Lottery: the Interplay of Overparameterisation and Curricula in Neural Networks
Stefano Mannelli, Yaraslau Ivashynka, Andrew Saxe et al.
Submodular framework for structured-sparse optimal transport
Piyushi Manupriya, Pratik Kumar Jawanpuria, Karthik Gurumoorthy et al.
Large Language Models are Geographically Biased
Rohin Manvi, Samar Khanna, Marshall Burke et al.
Towards General Neural Surrogate Solvers with Specialized Neural Accelerators
Chenkai Mao, Robert Lupoiu, Tianxiang Dai et al.
Regression with Multi-Expert Deferral
Anqi Mao, Mehryar Mohri, Yutao Zhong
No-Regret Reinforcement Learning in Smooth MDPs
Davide Maran, Alberto Maria Metelli, Matteo Papini et al.
Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows
Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling
Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi
On the Consistency of Kernel Methods with Dependent Observations
Pierre-François Massiani, Sebastian Trimpe, Friedrich Solowjow
Delving into Differentially Private Transformer
Youlong Ding, Xueyang Wu, Yining meng et al.
IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation
Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht et al.
Position: Tensor Networks are a Valuable Asset for Green AI
Eva Memmel, Clara Menzen, Jetze Schuurmans et al.
Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification
Yiming Meng, Ruikun Zhou, Amartya Mukherjee et al.
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics
Siqi Miao, Zhiyuan Lu, Mia Liu et al.
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data
Rui Miao, Kaixiong Zhou, Yili Wang et al.
CLIPZyme: Reaction-Conditioned Virtual Screening of Enzymes
Peter Mikhael, Itamar Chinn, Regina Barzilay
Understanding Retrieval-Augmented Task Adaptation for Vision-Language Models
Yifei Ming, Sharon Li
RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution Samples
Hossein Mirzaei, Mohammad Jafari Varnousfaderani, Hamid Reza Dehbashi et al.
Prodigy: An Expeditiously Adaptive Parameter-Free Learner
Konstantin Mishchenko, Aaron Defazio
Provable Interactive Learning with Hindsight Instruction Feedback
Dipendra Misra, Aldo Pacchiano, Robert Schapire
Straight-Through Meets Sparse Recovery: the Support Exploration Algorithm
Mimoun Mohamed, Francois Malgouyres, Valentin Emiya et al.
OAK: Enriching Document Representations using Auxiliary Knowledge for Extreme Classification
Shikhar Mohan, Deepak Saini, Anshul Mittal et al.
Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks
Bjørn Leth Møller, Christian Igel, Kristoffer Wickstrøm et al.
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Behrad Moniri, Donghwan Lee, Hamed Hassani et al.
Learning Optimal Deterministic Policies with Stochastic Policy Gradients
Alessandro Montenegro, Marco Mussi, Alberto Maria Metelli et al.
Position: Levels of AGI for Operationalizing Progress on the Path to AGI
Meredith Morris, Jascha Sohl-Dickstein, Noah Fiedel et al.
BAGEL: Bootstrapping Agents by Guiding Exploration with Language
Shikhar Murty, Christopher Manning, Peter Shaw et al.
Test-Time Regret Minimization in Meta Reinforcement Learning
Mirco Mutti, Aviv Tamar
Learning in Deep Factor Graphs with Gaussian Belief Propagation
Seth Nabarro, Mark van der Wilk, Andrew Davison
Equivariant Deep Weight Space Alignment
Aviv Navon, Aviv Shamsian, Ethan Fetaya et al.
Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Design
Quan Nguyen, Adji Bousso Dieng
Novel Spectral Algorithms for the Partial Credit Model
Duc Nguyen, Anderson Zhang
Sliced Wasserstein with Random-Path Projecting Directions
Khai Nguyen, Shujian Zhang, Tam Le et al.
Risk-Sensitive Reward-Free Reinforcement Learning with CVaR
Xinyi Ni, Guanlin Liu, Lifeng Lai
RNAFlow: RNA Structure & Sequence Design via Inverse Folding-Based Flow Matching
Divya Nori, Wengong Jin
Mixtures of Experts Unlock Parameter Scaling for Deep RL
Johan Obando Ceron, Ghada Sokar, Timon Willi et al.
Fair Resource Allocation in Multi-Task Learning
Hao Ban, Kaiyi Ji
Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?
Andreas Opedal, Alessandro Stolfo, Haruki Shirakami et al.
Structured Chemistry Reasoning with Large Language Models
Siru Ouyang, Zhuosheng Zhang, Bing Yan et al.
MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent
Kaan Ozkara, Can Karakus, Parameswaran Raman et al.
Stability and Generalization for Stochastic Recursive Momentum-based Algorithms for (Strongly-)Convex One to $K$-Level Stochastic Optimizations
Xiaokang Pan, Xingyu Li, Jin Liu et al.
RMIB: Representation Matching Information Bottleneck for Matching Text Representations
Haihui Pan, zhifang Liao, Wenrui Xie et al.
Auto-Encoding Morph-Tokens for Multimodal LLM
Kaihang Pan, Siliang Tang, Juncheng Li et al.
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization
Ashwinee Panda, Xinyu Tang, Saeed Mahloujifar et al.
Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulation
Xianghe Pang, shuo tang, Rui Ye et al.
Trainable Transformer in Transformer
Abhishek Panigrahi, Sadhika Malladi, Mengzhou Xia et al.
Position: Topological Deep Learning is the New Frontier for Relational Learning
Theodore Papamarkou, Tolga Birdal, Michael Bronstein et al.
The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm
Giseung Park, woohyeon Byeon, Seongmin Kim et al.
Mean-field Chaos Diffusion Models
Sungwoo Park, Dongjun Kim, Ahmed Alaa
BOtied: Multi-objective Bayesian optimization with tied multivariate ranks
Ji Won Park, Natasa Tagasovska, Michael Maser et al.
State-Free Inference of State-Space Models: The *Transfer Function* Approach
Rom N. Parnichkun, Stefano Massaroli, Alessandro Moro et al.
Variational Inference with Coverage Guarantees in Simulation-Based Inference
Yash Patel, Declan McNamara, Jackson Loper et al.
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler
Hongyi Peng, Han Yu, Xiaoli Tang et al.
Improving Diffusion Models for Inverse Problems Using Optimal Posterior Covariance
Xinyu Peng, Ziyang Zheng, Wenrui Dai et al.
A Subquadratic Time Algorithm for Robust Sparse Mean Estimation
Ankit Pensia
Interpreting and Improving Diffusion Models from an Optimization Perspective
Frank Permenter, Chenyang Yuan
Mechanistic Neural Networks for Scientific Machine Learning
Adeel Pervez, Francesco Locatello, Efstratios Gavves
Bayesian Regret Minimization in Offline Bandits
Marek Petrik, Guy Tennenholtz, Mohammad Ghavamzadeh
Cross-view Masked Diffusion Transformers for Person Image Synthesis
Trung Pham, Kang Zhang, Chang Yoo
Detecting Influence Structures in Multi-Agent Reinforcement Learning
Fabian Raoul Pieroth, Katherine Fitch, Lenz Belzner
Contrasting Multiple Representations with the Multi-Marginal Matching Gap
Zoe Piran, Michal Klein, James Thornton et al.
Mechanistic Design and Scaling of Hybrid Architectures
Michael Poli, Armin Thomas, Eric Nguyen et al.
Robust Data-driven Prescriptiveness Optimization
Mehran Poursoltani, Erick Delage, Angelos Georghiou
Learning Multiple Secrets in Mastermind
Milind Prabhu, David Woodruff
The Entropy Enigma: Success and Failure of Entropy Minimization
Ori Press, Ravid Shwartz-Ziv, Yann LeCun et al.
Learning-Efficient Yet Generalizable Collaborative Filtering for Item Recommendation
Yuanhao Pu, Xiaolong Chen, Xu Huang et al.
Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration
Shi-ang Qi, Yakun Yu, Russell Greiner
ULAREF: A Unified Label Refinement Framework for Learning with Inaccurate Supervision
Congyu Qiao, Ning Xu, Yihao Hu et al.
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes
Zhen Qin, Daoyuan Chen, Bingchen Qian et al.
Various Lengths, Constant Speed: Efficient Language Modeling with Lightning Attention
Zhen Qin, Weigao Sun, Dong Li et al.
Transferring Knowledge From Large Foundation Models to Small Downstream Models
Shikai Qiu, Boran Han, Danielle Robinson et al.
Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations
Helen Qu, Sang Michael Xie
Decomposable Submodular Maximization in Federated Setting
Akbar Rafiey
Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation
Ossi Räisä, Joonas Jälkö, Antti Honkela
STEER: Assessing the Economic Rationality of Large Language Models
Narun Raman, Taylor Lundy, Samuel Joseph Amouyal et al.
Position: The Reasonable Person Standard for AI
Sunayana Rane
Unveiling Privacy, Memorization, and Input Curvature Links
Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi et al.
Fair Federated Learning via the Proportional Veto Core
Bhaskar Ray Chaudhury, Aniket Murhekar, Zhuowen Yuan et al.
Optimal Batched Linear Bandits
Xuanfei Ren, Tianyuan Jin, Pan Xu
TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules
Weijieying Ren, Xiaoting Li, Huiyuan Chen et al.
Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks
Zach Robertson, Sanmi Koyejo
Position: Mission Critical – Satellite Data is a Distinct Modality in Machine Learning
Esther Rolf, Konstantin Klemmer, Caleb Robinson et al.
Invariant Risk Minimization Is A Total Variation Model
Zhao-Rong Lai, Weiwen Wang
Position: Application-Driven Innovation in Machine Learning
David Rolnick, Alan Aspuru-Guzik, Sara Beery et al.
One-Shot Strategic Classification Under Unknown Costs
Elan Rosenfeld, Nir Rosenfeld
Modelling Microbial Communities with Graph Neural Networks
Albane Ruaud, Cansu Sancaktar, Marco Bagatella et al.
Generalizing Orthogonalization for Models with Non-Linearities
David Rügamer, Chris Kolb, Tobias Weber et al.
Rolling Diffusion Models
David Ruhe, Jonathan Heek, Tim Salimans et al.
Second-Order Uncertainty Quantification: A Distance-Based Approach
Yusuf Sale, Viktor Bengs, Michele Caprio et al.
Predictive Coding beyond Correlations
Tommaso Salvatori, Luca Pinchetti, Amine M'Charrak et al.
Proactive Detection of Voice Cloning with Localized Watermarking
Robin San Roman, Pierre Fernandez, Hady Elsahar et al.
Sparse and Structured Hopfield Networks
Saúl Santos, Vlad Niculae, Daniel McNamee et al.
A fast algorithm to simulate nonlinear resistive networks
Benjamin Scellier
Parallel Affine Transformation Tuning of Markov Chain Monte Carlo
Philip Schär, Michael Habeck, Daniel Rudolf
Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models
Christian Schlarmann, Naman Singh, Francesco Croce et al.
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference
Marvin Schmitt, Desi Ivanova, Daniel Habermann et al.
Asymptotics of Learning with Deep Structured (Random) Features
Dominik Schröder, Daniil Dmitriev, Hugo Cui et al.