NeurIPS 2024: all accepted papers
← prev 1 … 40 41 42 43 44 45 next →
- Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner ↗Valentyn Melnychuk, Stefan Feuerriegel, Mihaela van der Schaar
- Quantifying and Optimizing Global Faithfulness in Persona-driven Role-playing ↗Letian Peng, Jingbo Shang
- Quantifying the Gain in Weak-to-Strong Generalization ↗Moses Charikar, Chirag Pabbaraju, Kirankumar Shiragur
- Quantitative Convergences of Lie Group Momentum Optimizers ↗Lingkai Kong, Molei Tao
- Quantum Algorithms for Non-smooth Non-convex Optimization ↗Chengchang Liu, Chaowen Guan, Jianhao He et al.
- Quantum algorithm for large-scale market equilibrium computation ↗Po‐Wei Huang, Patrick Rebentrost
- Quasi-Bayes meets Vines ↗David Huk, Yuanhe Zhang, Mark F. J. Steel et al.
- Query-Efficient Correlation Clustering with Noisy Oracle ↗Yuko Kuroki, Atsushi Miyauchi, Francesco Bonchi et al.
- Queueing Matching Bandits with Preference Feedback ↗Jung-hun Kim, Min-hwan Oh
- REDUCR: Robust Data Downsampling using Class Priority Reweighting ↗William Bankes, George Hughes, Ilija Bogunovic et al.
- RGMDT: Return-Gap-Minimizing Decision Tree Extraction in Non-Euclidean Metric Space ↗Jingdi Chen, Hanhan Zhou, Yongsheng Mei et al.
- ROIDICE: Offline Return on Investment Maximization for Efficient Decision Making ↗Woosung Kim, Hayeong Lee, Jongmin Lee et al.
- RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks ↗Guglielmo Gattiglio, Lyudmila Grigoryeva, Massimiliano Tamborrino
- Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding ↗Daniel Severo, Ashish J. Khisti, Alireza Makhzani
- Random Function Descent ↗Felix Benning, Leif Döring
- Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation ↗Wooseong Cho, Taehyun Hwang, Joongkyu Lee et al.
- Randomized Sparse Matrix Compression for Large-Scale Constrained Optimization in Cancer Radiotherapy ↗Shima Adeli, Mojtaba Tefagh, Gourav Jhanwar et al.
- Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces ↗Angeliki Kamoutsi, Peter Schmitt-Förster, Tobias Sutter et al.
- Rapid Plug-in Defenders ↗Kai Wu, Jing Liu, Jian Lou et al.
- ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization ↗Xiaoxing Wang, Xiaohan Qin, Xiaokang Yang et al.
- Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design ↗Ruisi Cai, Yeonju Ro, Geon-Woo Kim et al.
- Real-Time Recurrent Learning using Trace Units in Reinforcement Learning ↗Esraa Elelimy, Adam White, Michael Bowling et al.
- Real-Time Selection Under General Constraints via Predictive Inference ↗Yuyang Huo, Lu Lin, Haojie Ren et al.
- Real-time Core-Periphery Guided ViT with Smart Data Layout Selection on Mobile Devices ↗Zhihao Shu, Xiaowei Yu, Zihao Wu et al.
- Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training ↗Yanlai Yang, Matt Jones, Michael C. Mozer et al.
- Reciprocal Reward Influence Encourages Cooperation From Self-Interested Agents ↗John L. Zhou, Weizhe Hong, Jonathan C. Kao
- RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance ↗Zhicheng Sun, Zhen-Hao Yang, Yang Jin et al.
- Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery ↗Anand Gopalakrishnan, Aleksandar Stanić, Jürgen Schmidhuber et al.
- Recurrent neural network dynamical systems for biological vision ↗Wayne Wah Ming Soo, Aldo Battista, Puria Radmard et al.
- Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss ↗Yi-Shan Wu, Yijie Zhang, Badr-Eddine Chérief-Abdellatif et al.
- Reference Trustable Decoding: A Training-Free Augmentation Paradigm for Large Language Models ↗Luohe Shi, Yao Yao, Zuchao Li et al.
- Regression under demographic parity constraints via unlabeled post-processing ↗Gayane Taturyan, Evgenii Chzhen, Mohamed Hebiri
- Regularized Conditional Diffusion Model for Multi-Task Preference Alignment ↗Xudong Yu, Chenjia Bai, Haoran He et al.
- Reinforcement Learning with Adaptive Regularization for Safe Control of Critical Systems ↗Haozhe Tian, Homayoun Hamedmoghadam, Robert Noel Shorten et al.
- Reinforcement Learning with LTL and ω-Regular Objectives via Optimality-Preserving Translation to Average Rewards ↗Xuan-Bach D. Le, Dominik Wagner, Leon Witzman et al.
- Rejection via Learning Density Ratios ↗Alexander Soen, Hisham Husain, Philip Schulz et al.
- Relating Hopfield Networks to Episodic Control ↗Hugo Chateau-Laurent, Frédéric Alexandre
- Relational Verification Leaps Forward with RABBit ↗Tarun Suresh, Debangshu Banerjee, Gagandeep Singh
- Reliable Learning of Halfspaces under Gaussian Marginals ↗Ilias Diakonikolas, Lisheng Ren, Nikos Zarifis
- Remix-DiT: Mixing Diffusion Transformers for Multi-Expert Denoising ↗Gongfan Fang, Xinyin Ma, Xinchao Wang
- Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad ↗Sayantan Choudhury, Nazarii Tupitsa, Nicolas Loizou et al.
- Reparameterization invariance in approximate Bayesian inference ↗Hrittik Roy, Marco Miani, Carl Henrik Ek et al.
- Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling ↗Harry Jake Cunningham, Giorgio Giannone, Mingtian Zhang et al.
- Replicability in Learning: Geometric Partitions and KKM-Sperner Lemma ↗Jason Vander Woude, Peter Dixon, A. Pavan et al.
- Replicable Uniformity Testing ↗Sihan Liu, Christopher Ye
- Reranking Laws for Language Generation: A Communication-Theoretic Perspective ↗António Farinhas, Haau-Sing Li, André F. T. Martins
- Rethinking Deep Thinking: Stable Learning of Algorithms using Lipschitz Constraints ↗Jay Bear, Adam Prügel‐Bennett, Jonathon S. Hare
- Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment ↗Weichao Zhou, Wenchao Li
- Rethinking Parity Check Enhanced Symmetry-Preserving Ansatz ↗Ge Yan, Mengfei Ran, Ruocheng Wang et al.
- Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data ↗Zhilin Zhao, Longbing Cao, Xuhui Fan et al.
- Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference ↗Xunpeng Huang, Difan Zou, Hanze Dong et al.
- Revisiting motion information for RGB-Event tracking with MOT philosophy ↗Tianlu Zhang, Kurt Debattista, Jungong Han et al.
- Risk-sensitive control as inference with Rényi divergence ↗Kaito Ito, Kenji Kashima
- Robust Conformal Prediction Using Privileged Information ↗Shai Feldman, Yaniv Romano
- Robust Mixture Learning when Outliers Overwhelm Small Groups ↗Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel et al.
- Robust Offline Active Learning on Graphs ↗Yuanchen Wu, Yubai Yuan
- Robust Reinforcement Learning with General Utility ↗Ziyi Chen, Yan Tung Wen, Heng Huang et al.
- Robust Sparse Regression with Non-Isotropic Designs ↗Chih-Hung Liu, Gleb Novikov
- Robustly overfitting latents for flexible neural image compression ↗Yura Perugachi-Diaz, Arwin Gansekoele, Sandjai Bhulai
- Rule Extrapolation in Language Modeling: A Study of Compositional Generalization on OOD Prompts ↗Anna Mészáros, Szilvia Ujváry, Wieland Brendel et al.
- S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search ↗Gengmo Zhou, Zhen Wang, Yu Feng et al.
- S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization ↗Richard Zhu, Mathias Oster, Yuehaw Khoo
- SA3DIP: Segment Any 3D Instance with Potential 3D Priors ↗Xi Chen Yang, Xu Gu, Xi Chen Yang et al.
- SAMPa: Sharpness-aware Minimization Parallelized ↗Wanyun Xie, Thomas Pethick, Volkan Cevher
- SCRREAM : SCan, Register, REnder And Map: A Framework for Annotating Accurate and Dense 3D Indoor Scenes with a Benchmark ↗Hyunjun Jung, Weihang Li, Shun‐Cheng Wu et al.
- SEA: State-Exchange Attention for High-Fidelity Physics Based Transformers ↗Parsa Esmati, Amirhossein Dadashzadeh, Vahid Ardakani et al.
- SEL-BALD: Deep Bayesian Active Learning with Selective Labels ↗Ruijiang Gao, Mingzhang Yin, Maytal Saar‐Tsechansky
- SELMA: Learning and Merging Skill-Specific Text-to-Image Experts with Auto-Generated Data ↗Jialu Li, Jaemin Cho, Yi-Lin Sung et al.
- SETLEXSEM CHALLENGE: Using Set Operations to Evaluate the Lexical and Semantic Robustness of Language Models ↗Bardiya Akhbari, Manish Gawali, Nicholas Dronen
- SGD vs GD: Rank Deficiency in Linear Networks ↗Aditya Varre, Margarita Sagitova, Nicolas Flammarion
- SHDocs: A dataset, benchmark, and method to efficiently generate high-quality, real-world specular highlight data with near-perfect alignment ↗Jovin Leong, Ming Di Koa, Benjamin Cham et al.
- SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization ↗Tehila Dahan, Kfir Yehuda Levy
- SOI: Scaling Down Computational Complexity by Estimating Partial States of the Model ↗Grzegorz Stefański, Paweł Daniluk, Artur Szumaczuk et al.
- SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization ↗Shuchen Zhu, Boao Kong, Songtao Lu et al.
- SRFUND: A Multi-Granularity Hierarchical Structure Reconstruction Benchmark in Form Understanding ↗Jun Du, Yan Wang, Chenyu Liu et al.
- SS1: Accelerating Inference with Fast and Expressive Sketch Structured Transform ↗Kimia Saedi, Aditya Desai, Apoorv Walia et al.
- STONE: A Submodular Optimization Framework for Active 3D Object Detection ↗Ruiyu Mao, Sarthak Maharana, Rishabh Iyer et al.
- STk: A Scalable Module for Solving Top-k Problems ↗Hanchen Xia, Weidong Liu, Xiaojun Mao
- Safe Exploitative Play with Untrusted Type Beliefs ↗Tongxin Li, Tinashe Handina, Shaolei Ren et al.
- Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel ↗Jialin Li, Marta Zagórowska, Giulia De Pasquale et al.
- Safe and Efficient: A Primal-Dual Method for Offline Convex CMDPs under Partial Data Coverage ↗Haobo Zhang, Xiyue Peng, Honghao Wei et al.
- Safe and Sparse Newton Method for Entropic-Regularized Optimal Transport ↗Zihao Tang, Yixuan Qiu
- Safety through feedback in Constrained RL ↗Shashank Reddy Chirra, Pradeep Reddy Varakantham, Praveen Paruchuri
- Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning ↗Adhyyan Narang, Andrew Wagenmaker, Lillian J. Ratliff et al.
- Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut ↗Hongyu Cheng, Sammy Khalife, Barbara Fiedorowicz et al.
- Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models ↗Puqian Wang, Nikos Zarifis, Ilias Diakonikolas et al.
- Sample-Efficient Agnostic Boosting ↗Udaya Ghai, Karan Singh
- Sample-Efficient Private Learning of Mixtures of Gaussians ↗Hassan Ashtiani, Mahbod Majid, Shyam Narayanan
- Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes ↗Yunyue Wei, Vincent Zhuang, Saraswati Soedarmadji et al.
- Scalable Early Childhood Reading Performance Prediction ↗Zhongkai Shangguan, Zanming Huang, Eshed Ohn-Bar et al.
- Scalable Kernel Inverse Optimization ↗Youyuan Long, Tolga Ok, Pedro Zattoni Scroccaro et al.
- Scalable Optimization in the Modular Norm ↗Tim Large, Yang Liu, Minyoung Huh et al.
- Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits ↗Gennaro Gala, Cassio Polpo de Campos, Antonio Vergari et al.
- Scanning Trojaned Models Using Out-of-Distribution Samples ↗Hossein Mirzaei, Ali Ansari, Bahar Dibaei Nia et al.
- Schur Nets: exploiting local structure for equivariance in higher order graph neural networks ↗Qingqi Zhang, Ruize Xu, Risi Kondor
- Score-Optimal Diffusion Schedules ↗Christopher Bryant Williams, Andrew Campbell, Arnaud Doucet B et al.
- Score-based 3D molecule generation with neural fields ↗Matthieu Kirchmeyer, Pedro O. Pinheiro, Saeed Saremi
- Segmenting Watermarked Texts From Language Models ↗Xingchi Li, Guanxun Li, Xianyang Zhang
- Self-Supervised Adversarial Training via Diverse Augmented Queries and Self-Supervised Double Perturbation ↗Ruize Zhang, Sheng Tang, Juan Cao
← prev 1 … 40 41 42 43 44 45 next →
This page in Markdown → https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/2024/papers/page/43/