NeurIPS
Collection
Accepted papers for NeurIPS (Conference on Neural Information Processing Systems), one dataset per year. • 13 items • Updated
title stringlengths 14 183 | paper_url stringlengths 42 42 | authors listlengths 1 36 | type stringclasses 3
values | primary_area stringclasses 13
values | abstract large_stringlengths 246 3.6k | keywords listlengths 1 28 | TL;DR large_stringlengths 2 250 ⌀ | submission_number int64 1 29.3k | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 2
values | embedding listlengths 768 768 |
|---|---|---|---|---|---|---|---|---|---|---|---|
Time-o1: Time-Series Forecasting Needs Transformed Label Alignment | https://openreview.net/forum?id=RxWILaXuhb | [
"Hao Wang",
"Licheng Pan",
"Zhichao Chen",
"Xu Chen",
"Qingyang Dai",
"Lei Wang",
"Haoxuan Li",
"Zhouchen Lin"
] | Poster | applications | Training time-series forecasting models poses unique challenges in loss function design. Most existing approaches adopt temporal mean squared error, but this study reveals two critical limitations: (1) it ignores the presence of label autocorrelation, which biases it from the true label sequence likelihood; (2) it inv... | [
"Time-Series",
"Label Autocorrelation",
"Orthogonalization"
] | Learning to forecast in the transformed domain improves forecasting performance. | 29,297 | 2505.17847 | title_snapshot | [
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REVE: A Foundation Model for EEG - Adapting to Any Setup with Large-Scale Pretraining on 25,000 Subjects | https://openreview.net/forum?id=ZeFMtRBy4Z | [
"Yassine El Ouahidi",
"Jonathan Lys",
"Philipp Thölke",
"Nicolas Farrugia",
"Bastien Pasdeloup",
"Vincent Gripon",
"Karim Jerbi",
"Giulia Lioi"
] | Poster | neuroscience_and_cognitive_science | Foundation models have transformed AI by reducing reliance on task-specific data through large-scale pretraining. While successful in language and vision, their adoption in EEG has lagged due to the heterogeneity of public datasets, which are collected under varying protocols, devices, and electrode configurations. Exi... | [
"Foundation Model",
"EEG",
"SSL",
"BCI"
] | A scalable EEG foundation model leveraging 60,000+ hours of data, adaptable to any electrode setup, offering ready-to-use embeddings and state-of-the-art performance across diverse tasks. | 29,260 | 2510.21585 | title_snapshot | [
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ModHiFi: Identifying High Fidelity predictive components for Model Modification | https://openreview.net/forum?id=lClK4uBxSG | [
"Dhruva Kashyap",
"Chaitanya Murti",
"Pranav K Nayak",
"Tanay Narshana",
"Chiranjib Bhattacharyya"
] | Spotlight | deep_learning | Open weight models, which are ubiquitous, rarely provide access to their training data or loss function. This makes modifying such models for tasks such as pruning or unlearning, which are constrained by this unavailability, an active area of research. Existing techniques typically require gradients or ground-truth lab... | [
"Pruning",
"Machine Unlearning"
] | null | 29,227 | 2511.19566 | title_snapshot | [
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The Structure of Relation Decoding Linear Operators in Large Language Models | https://openreview.net/forum?id=XsBzmJzJ2l | [
"Miranda Anna Christ",
"Adrián Csiszárik",
"Gergely Becsó",
"Dániel Varga"
] | Spotlight | deep_learning | This paper investigates the structure of linear operators introduced in Hernandez et al. [2023] that decode specific relational facts in transformer language models. We extend their single-relation findings to a collection of relations and systematically chart their organization. We show that such collections of relati... | [
"large language models",
"relations",
"tensor networks",
"interpretability"
] | We investigate the structure of relations in large language models, and compress linear relation decoding operators with tensor networks | 29,206 | 2510.26543 | title_snapshot | [
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Vulnerable Data-Aware Adversarial Training | https://openreview.net/forum?id=yrrU5YChQr | [
"Yuqi Feng",
"Jiahao Fan",
"Yanan Sun"
] | Poster | deep_learning | Fast adversarial training (FAT) has been considered as one of the most effective alternatives to the computationally-intensive adversarial training. Generally, FAT methods pay equal attention to each sample of the target task. However, the distance between each sample and the decision boundary is different, learning sa... | [
"Adversarial Training",
"Adversarial Robustness",
"Decision Boundary Analysis"
] | null | 29,190 | null | null | [
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Tight analyses of first-order methods with error feedback | https://openreview.net/forum?id=hlPk6Hi43e | [
"Daniel Berg Thomsen",
"Adrien Taylor",
"Aymeric Dieuleveut"
] | Poster | optimization | Communication between agents often constitutes a major computational bottleneck in distributed learning. One of the most common mitigation strategies is to compress the information exchanged, thereby reducing communication overhead. To counteract the degradation in convergence associated with compressed communication, ... | [
"distributed optimization",
"distributed learning",
"error feedback",
"EF",
"EF21",
"tight analysis",
"performance estimation",
"convex optimization",
"large-scale machine learning"
] | null | 29,188 | 2506.05271 | title_snapshot | [
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Cost-Sensitive Freeze-thaw Bayesian Optimization for Efficient Hyperparameter Tuning | https://openreview.net/forum?id=ZUb4JpNoJe | [
"Dong Bok Lee",
"Aoxuan Silvia Zhang",
"Byungjoo Kim",
"Junhyeon Park",
"Steven Adriaensen",
"Juho Lee",
"Sung Ju Hwang",
"Hae Beom Lee"
] | Poster | deep_learning | In this paper, we address the problem of cost-sensitive hyperparameter optimization (HPO) built upon freeze-thaw Bayesian optimization (BO). Specifically, we assume a scenario where users want to early-stop the HPO process when the expected performance improvement is not satisfactory with respect to the additional comp... | [
"Cost-Sensitive",
"Bayesian Optimization",
"Multi-Fidelity HPO",
"PFNs",
"Transfer Learning"
] | null | 29,184 | 2510.21379 | title_snapshot | [
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... |
Novel Exploration via Orthogonality | https://openreview.net/forum?id=yJS1eZSNUv | [
"Andreas Theophilou",
"Özgür Şimşek"
] | Poster | reinforcement_learning | Efficient exploration remains one of the most important open problems in reinforcement learning. Discovering novel states or transitions requires policies that efficiently direct the agent away from the regions of the state space that are already well explored. We introduce Novel Exploration via Orthogonality (NEO), an... | [
"Laplacian",
"Novelty",
"Reinforcement Learning",
"Exploration",
"Eigenvectors",
"Spectral Methods"
] | We use Laplacian representation to improve exploration for reinforcement learning agents. | 29,178 | null | null | [
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-0.06570222228765488,
-0.... |
The Good, the Bad and the Ugly: Meta-Analysis of Watermarks, Transferable Attacks and Adversarial Defenses | https://openreview.net/forum?id=NVDrWBwJTV | [
"Grzegorz Gluch",
"Berkant Turan",
"Sai Ganesh Nagarajan",
"Sebastian Pokutta"
] | Poster | theory | We formalize and analyze the trade-off between backdoor-based watermarks and adversarial defenses, framing it as an interactive protocol between a verifier and a prover. While previous works have primarily focused on this trade-off, our analysis extends it by identifying transferable attacks as a third, counterintuitiv... | [
"Interactive Proof Systems",
"Cryptography",
"Backdoors",
"Game Theory",
"Learning Theory",
"Transferable Attacks",
"Adversarial Robustness"
] | null | 29,164 | 2410.08864 | title_snapshot | [
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0.0298505499958992,
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0... |
Improved Algorithms for Overlapping and Robust Clustering of Edge-Colored Hypergraphs: An LP-Based Combinatorial Approach | https://openreview.net/forum?id=F3DrgOZYc6 | [
"Changyeol Lee",
"Yongho Shin",
"Hyung-Chan An"
] | Poster | general_machine_learning | Clustering is a fundamental task in both machine learning and data mining. Among various methods, edge-colored clustering (ECC) has emerged as a useful approach for handling categorical data. Given a hypergraph with (hyper)edges labeled by colors, ECC aims to assign vertex colors to minimize the number of edges where t... | [
"overlapping edge-colored clustering",
"robust edge-colored clustering",
"edge-colored clustering",
"hypergraph clustering",
"primal-dual methods",
"approximation algorithms"
] | This paper presents improved algorithms for overlapping and robust clustering of edge-colored hypergraphs; our algorithms combine the strengths of LP with the efficiency of combinatorial algorithms, efficiently producing high-quality solutions. | 29,157 | 2505.18043 | title_snapshot | [
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-0.03083178587257862,
-0.029855700209736824,
-0.08138208836317062,
0.... |
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