Most Cited 2024 "3d hand estimation" Papers
12,324 papers found • Page 44 of 62
Conference
Sequential Representation Learning via Static-Dynamic Conditional Disentanglement
Mathieu Simon, Pascal Frossard, Christophe De Vleeschouwer
Test-Time Regret Minimization in Meta Reinforcement Learning
Mirco Mutti, Aviv Tamar
Best Arm Identification for Stochastic Rising Bandits
Marco Mussi, Alessandro Montenegro, Francesco Trovò et al.
Hypernetworks for Generalizable BRDF Representation
Fazilet Gokbudak, Alejandro Sztrajman, Chenliang Zhou et al.
Event-Based Motion Magnification
Yutian Chen, Shi Guo, Yu Fangzheng et al.
SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States
Noga Mudrik, Gal Mishne, Adam Charles
PFedEdit: Personalized Federated Learning via Automated Model Editing
Haolin Yuan, William Paul, John Aucott et al.
Rectify the Regression Bias in Long-Tailed Object Detection
Ke Zhu, Minghao Fu, Jie Shao et al.
AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale
Adam Pardyl, Michal Wronka, Maciej Wołczyk et al.
Straight-Through Meets Sparse Recovery: the Support Exploration Algorithm
Mimoun Mohamed, Francois Malgouyres, Valentin Emiya et al.
CoLA: Conditional Dropout and Language-driven Robust Dual-modal Salient Object Detection
Shuang Hao, Chunlin Zhong, He Tang
Neural-Kernel Conditional Mean Embeddings
Eiki Shimizu, Kenji Fukumizu, Dino Sejdinovic
De-Confusing Pseudo-Labels in Source-Free Domain Adaptation
Idit Diamant, Amir Rosenfeld, Idan Achituve et al.
From Inverse Optimization to Feasibility to ERM
Saurabh Mishra, Anant Raj, Sharan Vaswani
FlowCon: Out-of-Distribution Detection using Flow-based Contrastive Learning
Saandeep Aathreya, Shaun Canavan
AD3: Introducing a score for Anomaly Detection Dataset Difficulty assessment using VIADUCT dataset
Jan Lehr, Jan H Philipps, Alik Sargsyan et al.
Parameterized Projected Bellman Operator
Théo Vincent, Alberto Maria Metelli, Boris Belousov et al.
Learning to Remove Wrinkled Transparent Film with Polarized Prior
Jiaqi Tang, RUIZHENG WU, Xiaogang Xu et al.
Dyn-Adapter: Towards Disentangled Representation for Efficient Visual Recognition
Yurong Zhang, Honghao Chen, Zhang Xinyu et al.
Object-Aware Query Perturbation for Cross-Modal Image-Text Retrieval
Naoya Sogi, Takashi Shibata, Makoto Terao
Prior Specification for Bayesian Matrix Factorization via Prior Predictive Matching
Eliezer de Souza da Silva, Tomasz Kuśmierczyk, Marcelo Hartmann et al.
Roping in Uncertainty: Robustness and Regularization in Markov Games
Jeremy McMahan, Giovanni Artiglio, Qiaomin Xie
Scaling Few-Shot Learning for the Open World
Zhipeng Lin, Wenjing Yang, Haotian Wang et al.
ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression
Guangchi Fang, Qingyong Hu, Longguang Wang et al.
Learning Multi-Object Positional Relationships via Emergent Communication
Yicheng Feng, Boshi An, Zongqing Lu
Blind Image Deconvolution by Generative-based Kernel Prior and Initializer via Latent Encoding
Jiangtao Zhang, Zongsheng Yue, Hui Wang et al.
No-Regret Reinforcement Learning in Smooth MDPs
Davide Maran, Alberto Maria Metelli, Matteo Papini et al.
ReGround: Improving Textual and Spatial Grounding at No Cost
Phillip (Yuseung) Lee, Minhyuk Sung
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach
Shaopeng Fu, Di Wang
Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization
Qi Zhang, Yi Zhou, Ashley Prater-Bennette et al.
AugDETR: Improving Multi-scale Learning for Detection Transformer
Jinpeng Dong, Yutong Lin, Chen Li et al.
Depth on Demand: Streaming Dense Depth from a Low Frame Rate Active Sensor
Andrea Conti, Matteo Poggi, Valerio CAMBARERI et al.
Descanning: From Scanned to the Original Images with a Color Correction Diffusion Model
Junghun Cha, Ali Haider, Seoyun Yang et al.
RSL-BA: Rolling Shutter Line Bundle Adjustment
Yongcong Zhang, Bangyan Liao, Yifei Xue et al.
CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning
Erum Mushtaq, Duygu Nur Yaldiz, Yavuz Faruk Bakman et al.
MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation
Nianzu Yang, Kaipeng Zeng, Haotian Lu et al.
RoboMP$^2$: A Robotic Multimodal Perception-Planning Framework with Multimodal Large Language Models
Qi Lv, Hao Li, Xiang Deng et al.
Self-Training Room Layout via Geometry-aware Ray-casting
Bolivar Solarte, Chin-Hsuan Wu, Jin-Cheng Jhang et al.
On the Joint Interaction of Models, Data, and Features
Yiding Jiang, Christina Baek, J Kolter
OLLIE: Imitation Learning from Offline Pretraining to Online Finetuning
Sheng Yue, Xingyuan Hua, Ju Ren et al.
OMPO: A Unified Framework for RL under Policy and Dynamics Shifts
Yu Luo, Tianying Ji, Fuchun Sun et al.
Exploiting Symmetric Temporally Sparse BPTT for Efficient RNN Training
Xi Chen, Chang Gao, Zuowen Wang et al.
Swift-Mapping: Online Neural Implicit Dense Mapping in Urban Scenes
Ke Wu, Kaizhao Zhang, Mingzhe Gao et al.
A Primal-Dual Approach to Solving Variational Inequalities with General Constraints
Tatjana Chavdarova, Tong Yang, Matteo Pagliardini et al.
Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language Models
Shuai Fu, Shuai Fu, Xiequn Wang et al.
Efficient Inverse Multiagent Learning
Denizalp Goktas, Amy Greenwald, Sadie Zhao et al.
Versatile Navigation Under Partial Observability via Value-guided Diffusion Policy
Gengyu Zhang, Hao Tang, Yan Yan
Adversarial Attacks on Federated-Learned Adaptive Bitrate Algorithms
Ruixiao Zhang, Tianchi Huang
Improving Subject-Driven Image Synthesis with Subject-Agnostic Guidance
Kelvin C.K. Chan, Yang Zhao, Xuhui Jia et al.
Standardized Interpretable Fairness Measures for Continuous Risk Scores
Ann-Kristin Becker, Oana Dumitrasc, Klaus Broelemann
Efficient Learning of Event-based Dense Representation using Hierarchical Memories with Adaptive Update
Uday Kamal, Saibal Mukhopadhyay
Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach
Sagar Shrestha, Xiao Fu
DecentNeRFs: Decentralized Neural Radiance Fields from Crowdsourced Images
Zaid Tasneem, Akshat Dave, Abhishek Singh et al.
Exploring Guided Sampling of Conditional GANs
Yifei Zhang, Mengfei Xia, Yujun Shen et al.
Perfect Alignment May be Poisonous to Graph Contrastive Learning
Jingyu Liu, Huayi Tang, Yong Liu
Fine Structure-Aware Sampling: A New Sampling Training Scheme for Pixel-Aligned Implicit Models in Single-View Human Reconstruction
K. Chan, Fayao Liu, Guosheng Lin et al.
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs
Milan Papez, Martin Rektoris, Vaclav Smidl et al.
No Head Left Behind – Multi-Head Alignment Distillation for Transformers
Tianyang Zhao, Kunwar Singh, Srikar Appalaraju et al.
Understanding the Training Speedup from Sampling with Approximate Losses
Rudrajit Das, Xi Chen, Bertram Ieong et al.
A Cephalometric Landmark Regression Method based on Dual-encoder for High-resolution X-ray Image
Chao Dai, Wang Yang, Chaolin Huang et al.
Enhancing Quality of Compressed Images by Mitigating Enhancement Bias Towards Compression Domain
Qunliang Xing, Mai Xu, Shengxi Li et al.
On the generalization capacity of neural networks during generic multimodal reasoning
Takuya Ito, Soham Dan, Mattia Rigotti et al.
NeRMo: Learning Implicit Neural Representations for 3D Human Motion Prediction
Dong Wei, Huaijiang Sun, Xiaoning Sun et al.
Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization
Neelkamal Bhuyan, Debankur Mukherjee, Adam Wierman
Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion
Xuantong Liu, Tianyang Hu, Wenjia Wang et al.
CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection
Jiayi Zhu, Qing Guo, Felix Juefei Xu et al.
Locally Adaptive Neural 3D Morphable Models
Michail Tarasiou, Rolandos Alexandros Potamias, Eimear O' Sullivan et al.
Improving Hyperbolic Representations via Gromov-Wasserstein Regularization
yifei Yang, Wonjun Lee, Dongmian Zou et al.
Path Choice Matters for Clear Attributions in Path Methods
Borui Zhang, Wenzhao Zheng, Jie Zhou et al.
PAC-Bayes Generalisation Bounds for Dynamical Systems including Stable RNNs
Deividas Eringis, John Leth, Zheng-Hua Tan et al.
Omniview-Tuning: Boosting Viewpoint Invariance of Vision-Language Pre-training Models
Shouwei Ruan, Yinpeng Dong, Liu Hanqing et al.
Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models
Songtao Liu, Hanjun Dai, Yue Zhao et al.
Personalized Reinforcement Learning with a Budget of Policies
Dmitry Ivanov, Omer Ben-Porat
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck Models
Nishad Singhi, Jae Myung Kim, Karsten Roth et al.
Pose-Guided Self-Training with Two-Stage Clustering for Unsupervised Landmark Discovery
Siddharth Tourani, Ahmed Alwheibi, Arif Mahmood et al.
Multiobjective Lipschitz Bandits under Lexicographic Ordering
Bo Xue, Ji Cheng, Fei Liu et al.
Anomaly Score: Evaluating Generative Models and Individual Generated Images based on Complexity and Vulnerability
Jaehui Hwang, Junghyuk Lee, Jong-Seok Lee
I2-SLAM: Inverting Imaging Process for Robust Photorealistic Dense SLAM
Gwangtak Bae, Changwoon Choi, Hyeongjun Heo et al.
Data Adaptive Traceback for Vision-Language Foundation Models in Image Classification
Long-Fei Li, Peng Zhao, Zhi-Hua Zhou
Enhancing Cross-Modal Fine-Tuning with Gradually Intermediate Modality Generation
Lincan Cai, Shuang Li, Wenxuan Ma et al.
Discrete Cycle-Consistency Based Unsupervised Deep Graph Matching
Siddharth Tourani, Muhammad Haris Khan, Carsten Rother et al.
SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder
Dihan Zheng, Yihang Zou, Xiaowen Zhang et al.
denoiSplit: a method for joint microscopy image splitting and unsupervised denoising
Ashesh Ashesh, Florian Jug
PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images
Jinsung Jeon, Hyundong Jin, Jonghyun Choi et al.
SRPose: Two-view Relative Pose Estimation with Sparse Keypoints
Rui Yin, Yulun Zhang, Zherong Pan et al.
Fast Value Tracking for Deep Reinforcement Learning
Frank Shih, Faming Liang
Multiplane Prior Guided Few-Shot Aerial Scene Rendering
Zihan Gao, Licheng Jiao, Lingling Li et al.
Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning
Joshua C. Zhao, Ahaan Dabholkar, Atul Sharma et al.
DECIDER: Leveraging Foundation Model Priors for Improved Model Failure Detection and Explanation
Rakshith Subramanyam, Kowshik Thopalli, Vivek Sivaraman Narayanaswamy et al.
12087 Limitations of Face Image Generation
Harrison Rosenberg, Shimaa Ahmed, Guruprasad Ramesh et al.
Robustness Verification of Deep Reinforcement Learning Based Control Systems Using Reward
Dapeng Zhi, Peixin Wang, Cheng Chen et al.
Progressive Classifier and Feature Extractor Adaptation for Unsupervised Domain Adaptation on Point Clouds
Zicheng Wang, Zhen Zhao, Yiming Wu et al.
EcoMatcher: Efficient Clustering Oriented Matcher for Detector-free Image Matching
Peiqi Chen, Lei Yu, Yi Wan et al.
Efficient Learning in Polyhedral Games via Best-Response Oracles
Darshan Chakrabarti, Gabriele Farina, Christian Kroer
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
Wei-Ning Chen, Berivan Isik, Peter Kairouz et al.
Ahpatron: A New Budgeted Online Kernel Learning Machine with Tighter Mistake Bound
Yun Liao, Junfan Li, Shizhong Liao et al.
Improving Factual Error Correction by Learning to Inject Factual Errors
Xingwei He, Qianru Zhang, A-Long Jin et al.
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank
Mouxiang Chen, Chenghao Liu, Zemin Liu et al.
s-ID: Causal Effect Identification in a Sub-population
Amir Mohammad Abouei, Ehsan Mokhtarian, Negar Kiyavash
A Fast and Provable Algorithm for Sparse Phase Retrieval
Jian-Feng Cai, Yu Long, Ruixue WEN et al.
Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy
Yingyu Lin, Yian Ma, Yu-Xiang Wang et al.
Combining Experimental and Historical Data for Policy Evaluation
Ting Li, Chengchun Shi, Qianglin Wen et al.
One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models
Sheng-Jun Huang, Yi Li, Yiming Sun et al.
Distilling Knowledge from Large-Scale Image Models for Object Detection
Gang Li, Wenhai Wang, Xiang Li et al.
Learning Trimodal Relation for Audio-Visual Question Answering with Missing Modality
Kyu Ri Park, Hong Joo Lee, Jung Uk Kim
Text2QR: Harmonizing Aesthetic Customization and Scanning Robustness for Text-Guided QR Code Generation
Guangyang Wu, Xiaohong Liu, Jun Jia et al.
Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning
Johnathan Xie, Yoonho Lee, Annie Chen et al.
SAIR: Learning Semantic-aware Implicit Representation
Canyu Zhang, Xiaoguang Li, Qing Guo et al.
Preventing Model Collapse in Gaussian Process Latent Variable Models
Ying Li, Zhidi Lin, Feng Yin et al.
Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning
Yeongwoo Song, Hawoong Jeong
Real-Time Neural BRDF with Spherically Distributed Primitives
Yishun Dou, Zhong Zheng, Qiaoqiao Jin et al.
UniPTS: A Unified Framework for Proficient Post-Training Sparsity
JingJing Xie, Yuxin Zhang, Mingbao Lin et al.
AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation
Zihao Tang, Zheqi Lv, Shengyu Zhang et al.
Layer-Wise Representation Fusion for Compositional Generalization
Yafang Zheng, Lei Lin, Shuangtao Li et al.
Unify Named Entity Recognition Scenarios via Contrastive Real-Time Updating Prototype
Yanhe Liu, Peng Wang, Ke Wenjun et al.
ExMap: Leveraging Explainability Heatmaps for Unsupervised Group Robustness to Spurious Correlations
Rwiddhi Chakraborty, Adrian de Sena Sletten, Michael C. Kampffmeyer
Atom-Level Optical Chemical Structure Recognition with Limited Supervision
Martijn Oldenhof, Edward De Brouwer, Adam Arany et al.
Decoupled Training: Return of Frustratingly Easy Multi-Domain Learning
Ximei Wang, Junwei Pan, Xingzhuo Guo et al.
Temporal Generalization Estimation in Evolving Graphs
Bin Lu, Tingyan Ma, Xiaoying Gan et al.
A Graph Dynamics Prior for Relational Inference
Liming Pan, Cheng Shi, Ivan Dokmanic
Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts
Shengzhuang Chen, Jihoon Tack, Yunqiao Yang et al.
Graph As Point Set
Xiyuan Wang, Pan Li, Muhan Zhang
Online Variational Sequential Monte Carlo
Alessandro Mastrototaro, Jimmy Olsson
Differentiable Model Scaling using Differentiable Topk
Kai Liu, Ruohui Wang, Jianfei Gao et al.
Bayesian Exploration Networks
Mattie Fellows, Brandon Kaplowitz, Christian Schroeder de Witt et al.
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need
Shangda Yang, Vitaly Zankin, Maximilian Balandat et al.
Agnostic Sample Compression Schemes for Regression
Idan Attias, Steve Hanneke, Aryeh Kontorovich et al.
Slicing Mutual Information Generalization Bounds for Neural Networks
Kimia Nadjahi, Kristjan Greenewald, Rickard Gabrielsson et al.
Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining
Aaron Li, Robin Netzorg, Zhihan Cheng et al.
Generalization Error of Graph Neural Networks in the Mean-field Regime
Gholamali Aminian, Yixuan He, Gesine Reinert et al.
A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models
Taehong Moon, Moonseok Choi, EungGu Yun et al.
Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles
Bhrij Patel, Wesley A. Suttle, Alec Koppel et al.
diff History for Neural Language Agents
Ulyana Piterbarg, Lerrel Pinto, Rob Fergus
A Field Guide for Pacing Budget and ROS Constraints
Santiago Balseiro, Kshipra Bhawalkar, Zhe Feng et al.
Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization
Kwang-Sung Jun, Jungtaek Kim
Deconstructing the Goldilocks Zone of Neural Network Initialization
Artem Vysogorets, Anna Dawid, Julia Kempe
Neural NeRF Compression
Tuan Pham, Stephan Mandt
LAGMA: LAtent Goal-guided Multi-Agent Reinforcement Learning
Hyungho Na, IL CHUL MOON
On the Second-Order Convergence of Biased Policy Gradient Algorithms
Siqiao Mu, Diego Klabjan
Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States
Noam Razin, Yotam Alexander, Edo Cohen-Karlik et al.
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer
Chang Chen, Junyeob Baek, Fei Deng et al.
The Merit of River Network Topology for Neural Flood Forecasting
Nikolas Kirschstein, Yixuan Sun
Listening to the noise: Blind Denoising with Gibbs Diffusion
David Heurtel-Depeiges, Charles Margossian, Ruben Ohana et al.
Learning Decision Trees and Forests with Algorithmic Recourse
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi et al.
Mimicking Better by Matching the Approximate Action Distribution
Joao A. Candido Ramos, Lionel Blondé, Naoya Takeishi et al.
Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought
Zhen-Yu Zhang, Siwei Han, Huaxiu Yao et al.
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses
Adel Javanmard, Matthew Fahrbach, Vahab Mirrokni
Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network
Hyunseok Oh, Youngki Lee
Continuous Treatment Effects with Surrogate Outcomes
Zhenghao Zeng, David Arbour, Avi Feller et al.
A Fixed-Point Approach for Causal Generative Modeling
Meyer Scetbon, Joel Jennings, Agrin Hilmkil et al.
Theoretical Analysis of Learned Database Operations under Distribution Shift through Distribution Learnability
Sepanta Zeighami, Cyrus Shahabi
Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits
Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun
Distributional Bellman Operators over Mean Embeddings
Li Kevin Wenliang, Gregoire Deletang, Matthew Aitchison et al.
Quantum Theory and Application of Contextual Optimal Transport
Nicola Mariella, Albert Akhriev, Francesco Tacchino et al.
Gambling-Based Confidence Sequences for Bounded Random Vectors
Jongha (Jon) Ryu, Gregory Wornell
From Classification Accuracy to Proper Scoring Rules: Elicitability of Probabilistic Top List Predictions
Johannes Resin
CF-OPT: Counterfactual Explanations for Structured Prediction
Germain Vivier-Ardisson, Alexandre Forel, Axel Parmentier et al.
Sparse Dimensionality Reduction Revisited
Mikael Møller Høgsgaard, Lior Kamma, Kasper Green Larsen et al.
Learning to Infer Generative Template Programs for Visual Concepts
R. Kenny Jones, Siddhartha Chaudhuri, Daniel Ritchie
Self-Supervised Interpretable End-to-End Learning via Latent Functional Modularity
Hyunki Seong, Hyunchul Shim
Local Feature Selection without Label or Feature Leakage for Interpretable Machine Learning Predictions
Harrie Oosterhuis, Lijun Lyu, Avishek Anand
On Stronger Computational Separations Between Multimodal and Unimodal Machine Learning
Ari Karchmer
Unveiling the Dynamics of Information Interplay in Supervised Learning
Kun Song, Zhiquan Tan, Bochao Zou et al.
GFlowNet Training by Policy Gradients
Puhua Niu, Shili Wu, Mingzhou Fan et al.
Joint Composite Latent Space Bayesian Optimization
Natalie Maus, Zhiyuan Jerry Lin, Maximilian Balandat et al.
Transitional Uncertainty with Layered Intermediate Predictions
Ryan Benkert, Mohit Prabhushankar, Ghassan AlRegib
GATE: How to Keep Out Intrusive Neighbors
Nimrah Mustafa, Rebekka Burkholz
ELF: Encoding Speaker-Specific Latent Speech Feature for Speech Synthesis
Jungil Kong, Junmo Lee, Jeongmin Kim et al.
Evaluating Model Bias Requires Characterizing its Mistakes
Isabela Albuquerque, Jessica Schrouff, David Warde-Farley et al.
Integrated Hardware Architecture and Device Placement Search
Irene Wang, Jakub Tarnawski, Amar Phanishayee et al.
Indirectly Parameterized Concrete Autoencoders
Alfred Nilsson, Klas Wijk, Sai bharath chandra Gutha et al.
Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization
Hao Wang, Kaifeng Yang, Michael Affenzeller
Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data
Yvonne Zhou, Mingyu Liang, Ivan Brugere et al.
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization
Sam Reifenstein, Timothee Leleu, Yoshihisa Yamamoto
Risk Aware Benchmarking of Large Language Models
Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti et al.
On Gradient-like Explanation under a Black-box Setting: When Black-box Explanations Become as Good as White-box
Yi Cai, Gerhard Wunder
Quality-Diversity with Limited Resources
Ren-Jian Wang, Ke Xue, Cong Guan et al.
Directly Denoising Diffusion Models
Dan Zhang, Jingjing Wang, Feng Luo
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
Jiayi Wang, Shiqiang Wang, Rong-Rong Chen et al.
Discovering Multiple Solutions from a Single Task in Offline Reinforcement Learning
Takayuki Osa, Tatsuya Harada
Saliency strikes back: How filtering out high frequencies improves white-box explanations
Sabine Muzellec, Thomas FEL, Victor Boutin et al.
Efficient Mixture Learning in Black-Box Variational Inference
Alexandra Hotti, Oskar Kviman, Ricky Molén et al.
Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training
Tehila Dahan, Kfir Levy
Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities
Golnoosh Farnadi, Mohammad Havaei, Negar Rostamzadeh
Et Tu Certifications: Robustness Certificates Yield Better Adversarial Examples
Andrew C. Cullen, Shijie Liu, Paul Montague et al.
Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching
Rico Angell, Andrew McCallum
Disentanglement Learning via Topology
Nikita Balabin, Daria Voronkova, Ilya Trofimov et al.
SFC: Achieve Accurate Fast Convolution under Low-precision Arithmetic
Liulu He, yufei zhao, rui gao et al.
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method
Qinghua Tao, Francesco Tonin, Alex Lambert et al.
Subhomogeneous Deep Equilibrium Models
Pietro Sittoni, Francesco Tudisco
Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency
Alan Amin, Andrew Wilson
Monte Carlo Tree Search in the Presence of Transition Uncertainty
Farnaz Kohankhaki, Kiarash Aghakasiri, Hongming Zhang et al.
Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates
Zhuanghua Liu, Luo Luo, Bryan Kian Hsiang Low
Towards Poisoning Fair Representations
Tianci Liu, Haoyu Wang, Feijie Wu et al.
Detection-Based Intermediate Supervision for Visual Question Answering
Yuhang Liu, Daowan Peng, Wei Wei et al.
SALSA: Semantically-Aware Latent Space Autoencoder
Kathryn Kirchoff, Travis Maxfield, Alexander Tropsha et al.
In-distribution Public Data Synthesis with Diffusion Models for Differentially Private Image Classification
Jinseong Park, Yujin Choi, Jaewook Lee
Learning Uncertainty-Aware Temporally-Extended Actions
Joongkyu Lee, Seung Joon Park, Yunhao Tang et al.
FaceCom: Towards High-fidelity 3D Facial Shape Completion via Optimization and Inpainting Guidance
Yinglong Li, Hongyu Wu, Wang et al.
Decoupling Representation and Knowledge for Few-Shot Intent Classification and Slot Filling
Jie Han, Yixiong Zou, Haozhao Wang et al.