NeurIPS 2023 Conference Submissions

On Generalization Bounds for Projective Clustering
Maria Sofia Bucarelli, Matilde Fjeldsø Larsen, Chris Schwiegelshohn, Mads Toftrup
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
A Combinatorial Algorithm for Approximating the Optimal Transport in the Parallel and MPC Settings
Nathaniel Lahn, Sharath Raghvendra, Kaiyi Zhang
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
Rethinking the Role of Token Retrieval in Multi-Vector Retrieval
Jinhyuk Lee, Zhuyun Dai, Sai Meher Karthik Duddu, Tao Lei, Iftekhar Naim, Ming-Wei Chang, Vincent Y Zhao
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
QuIP: 2-Bit Quantization of Large Language Models With Guarantees
Jerry Chee, Yaohui Cai, Volodymyr Kuleshov, Christopher De Sa
- Published: 21 Sept 2023, Last Modified: 15 Jan 2024
- NeurIPS 2023 spotlight
- Readers: Everyone
Deep Equilibrium Based Neural Operators for Steady-State PDEs
Tanya Marwah, Ashwini Pokle, J Zico Kolter, Zachary Chase Lipton, Jianfeng Lu, Andrej Risteski
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
Parallel Sampling of Diffusion Models
Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, Nima Anari
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 spotlight
- Readers: Everyone
Percentile Criterion Optimization in Offline Reinforcement Learning
Cyrus Cousins, Elita Lobo, Marek Petrik, Yair Zick
- Published: 21 Sept 2023, Last Modified: 16 Jan 2024
- NeurIPS 2023 poster
- Readers: Everyone
Approximately Equivariant Graph Networks
Ningyuan Teresa Huang, Ron Levie, Soledad Villar
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
Using Imperfect Surrogates for Downstream Inference: Design-based Supervised Learning for Social Science Applications of Large Language Models
Naoki Egami, Musashi Hinck, Brandon M. Stewart, Hanying Wei
- Published: 21 Sept 2023, Last Modified: 14 Jan 2024
- NeurIPS 2023 poster
- Readers: Everyone
Preference-grounded Token-level Guidance for Language Model Fine-tuning
Shentao Yang, Shujian Zhang, Congying Xia, Yihao Feng, Caiming Xiong, Mingyuan Zhou
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
GNNEvaluator: Evaluating GNN Performance On Unseen Graphs Without Labels
Xin Zheng, Miao Zhang, Chunyang Chen, Soheila Molaei, Chuan Zhou, Shirui Pan
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
Structure-free Graph Condensation: From Large-scale Graphs to Condensed Graph-free Data
Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 spotlight
- Readers: Everyone
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks
Daogao Liu, Arun Ganesh, Sewoong Oh, Abhradeep Guha Thakurta
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 spotlight
- Readers: Everyone
Where Did I Come From? Origin Attribution of AI-Generated Images
Zhenting Wang, Chen Chen, Yi Zeng, Lingjuan Lyu, Shiqing Ma
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
Your representations are in the network: composable and parallel adaptation for large scale models
Yonatan Dukler, Alessandro Achille, Hao Yang, Varsha Vivek, Luca Zancato, Benjamin Bowman, Avinash Ravichandran, Charless Fowlkes, Ashwin Swaminathan, Stefano Soatto
- Published: 21 Sept 2023, Last Modified: 19 Jan 2024
- NeurIPS 2023 poster
- Readers: Everyone
Faster Relative Entropy Coding with Greedy Rejection Coding
Gergely Flamich, Stratis Markou, José Miguel Hernández-Lobato
- Published: 21 Sept 2023, Last Modified: 05 Jan 2024
- NeurIPS 2023 poster
- Readers: Everyone
Visual Instruction Tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, Yong Jae Lee
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 oral
- Readers: Everyone
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems
Chaoyue Liu, Dmitriy Drusvyatskiy, Misha Belkin, Damek Davis, Yian Ma
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
Near-Optimal $k$-Clustering in the Sliding Window Model
David Woodruff, Peilin Zhong, Samson Zhou
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM
Ziba Parsons, Fei Dou, Houyi Du, Zheng Song, Jin Lu
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
Privacy-Preserving CNN Training with Transfer Learning
Li-Yue Sun
- 09 May 2023 (modified: 12 Dec 2023)
- Submitted to NeurIPS 2023
- Readers: Everyone
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
Laixi Shi, Gen Li, Yuting Wei, Yuxin Chen, Matthieu Geist, Yuejie Chi
- Published: 21 Sept 2023, Last Modified: 09 Jan 2024
- NeurIPS 2023 poster
- Readers: Everyone
Reconstructing the Mind's Eye: fMRI-to-Image with Contrastive Learning and Diffusion Priors
Paul Steven Scotti, Atmadeep Banerjee, Jimmie Goode, Stepan Shabalin, Alex Nguyen, Cohen Ethan, Aidan James Dempster, Nathalie Verlinde, Elad Yundler, David Weisberg, Kenneth Norman, Tanishq Mathew Abraham
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 spotlight
- Readers: Everyone
Fast Asymptotically Optimal Algorithms for Non-Parametric Stochastic Bandits
Dorian Baudry, Fabien Pesquerel, Rémy Degenne, Odalric-Ambrym Maillard
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 poster
- Readers: Everyone
Survival Instinct in Offline Reinforcement Learning
Anqi Li, Dipendra Misra, Andrey Kolobov, Ching-An Cheng
- Published: 21 Sept 2023, Last Modified: 02 Nov 2023
- NeurIPS 2023 spotlight
- Readers: Everyone