NeurIPS
Collection
Accepted papers for NeurIPS (Conference on Neural Information Processing Systems), one dataset per year. • 13 items • Updated
title stringlengths 17 149 | paper_url stringlengths 42 42 | authors listlengths 1 34 | type stringclasses 3
values | primary_area stringclasses 31
values | abstract large_stringlengths 468 2.59k | keywords listlengths 1 17 | TL;DR large_stringlengths 4 250 ⌀ | submission_number int64 3 21.8k | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 2
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|---|---|---|---|---|---|---|---|---|---|---|---|
No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery | https://openreview.net/forum?id=iEeiZlTbts | [
"Alexander Rutherford",
"Michael Beukman",
"Timon Willi",
"Bruno Lacerda",
"Nick Hawes",
"Jakob Nicolaus Foerster"
] | Poster | reinforcement_learning | What data or environments to use for training to improve downstream performance is a longstanding and very topical question in reinforcement learning.
In particular, Unsupervised Environment Design (UED) methods have gained recent attention as their adaptive curricula promise to enable agents to be robust to in- and o... | [
"MARL",
"UED",
"Robotics"
] | An improved score function for unsupervised environment design in binary outcome settings, which we use to train agents for real-world tasks, and an improved adversarial evaluation protocol that assesses policy robustness. | 21,766 | 2408.15099 | title_snapshot | [
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Autoregressive Image Diffusion: Generation of Image Sequence and Application in MRI | https://openreview.net/forum?id=jIh4W7r0rn | [
"Guanxiong Luo",
"Shoujin Huang",
"Martin Uecker"
] | Poster | machine_learning_for_healthcare | Magnetic resonance imaging (MRI) is a widely used non-invasive imaging modality. However, a persistent challenge lies in balancing image quality with imaging speed. This trade-off is primarily constrained by k-space measurements, which traverse specific trajectories in the spatial Fourier domain (k-space). These measu... | [
"Autoregressive models",
"Diffusion models",
"Inverse problems",
"Medical imaging",
"MRI"
] | null | 21,747 | 2405.14327 | title_snapshot | [
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The Implicit Bias of Gradient Descent on Separable Multiclass Data | https://openreview.net/forum?id=JlWn80mTJi | [
"Hrithik Ravi",
"Clayton Scott",
"Daniel Soudry",
"Yutong Wang"
] | Poster | learning_theory | Implicit bias describes the phenomenon where optimization-based training algorithms, without explicit regularization, show a preference for simple estimators even when more complex estimators have equal objective values. Multiple works have developed the theory of implicit bias for binary classification under the assum... | [
"gradient descent",
"multiclass classification",
"hard-margin SVM",
"implicit bias"
] | We prove implicit bias of gradient descent for linearly separable multiclass problems. | 21,665 | 2411.01350 | title_snapshot | [
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How many classifiers do we need? | https://openreview.net/forum?id=m5dyKArVn8 | [
"Hyunsuk Kim",
"Liam Hodgkinson",
"Ryan Theisen",
"Michael W. Mahoney"
] | Poster | learning_theory | As performance gains through scaling data and/or model size experience diminishing returns, it is becoming increasingly popular to turn to ensembling, where the predictions of multiple models are combined to improve accuracy.
In this paper, we provide a detailed analysis of how the disagreement and the polarization (a... | [
"ensemble",
"model aggregation",
"machine learning",
"computer vision"
] | We develop bounds on the majority vote error that are tight enough to predict ensemble performance. | 21,653 | 2411.00328 | title_snapshot | [
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Learning to Reason via Program Generation, Emulation, and Search | https://openreview.net/forum?id=te6VagJf6G | [
"Nathaniel Weir",
"Muhammad Khalifa",
"Linlu Qiu",
"Orion Weller",
"Peter Clark"
] | Poster | natural_language_processing | Program synthesis with language models (LMs) has unlocked a large set of reasoning abilities; code-tuned LMs have proven adept at generating programs that solve a wide variety of algorithmic symbolic manipulation tasks (e.g. word concatenation). However, not all reasoning tasks are easily expressible as code, e.g. task... | [
"language models",
"instruction tuning",
"code generation",
"reasoning",
"program search",
"program emulation"
] | We show that fine-tuning LMs to generate and then emulate the execution of programs creates models can learn new tasks via program search. | 21,651 | 2405.16337 | title_snapshot | [
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Beyond the Doors of Perception: Vision Transformers Represent Relations Between Objects | https://openreview.net/forum?id=8puv3c9CPg | [
"Michael A. Lepori",
"Alexa R. Tartaglini",
"Wai Keen Vong",
"Thomas Serre",
"Brenden Lake",
"Ellie Pavlick"
] | Poster | interpretability_and_explainability | Though vision transformers (ViTs) have achieved state-of-the-art performance in a variety of settings, they exhibit surprising failures when performing tasks involving visual relations. This begs the question: how do ViTs attempt to perform tasks that require computing visual relations between objects? Prior efforts to... | [
"visual reasoning",
"mechanistic interpretability",
"transformers",
"cognitive science"
] | We use methods from mechanistic interpretability to investigate how Vision Transformers perform an abstract visual reasoning task. | 21,637 | 2406.15955 | title_snapshot | [
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FactorizePhys: Matrix Factorization for Multidimensional Attention in Remote Physiological Sensing | https://openreview.net/forum?id=qrfp4eeZ47 | [
"Jitesh Joshi",
"Sos Agaian",
"Youngjun Cho"
] | Poster | deep_learning_architectures | Remote photoplethysmography (rPPG) enables non-invasive extraction of blood volume pulse signals through imaging, transforming spatial-temporal data into time series signals. Advances in end-to-end rPPG approaches have focused on this transformation where attention mechanisms are crucial for feature extraction. However... | [
"Time-series estimation",
"remote photo-plethysmography",
"spatial-temporal attention",
"non-negative matrix factorization"
] | This work introduces the Factorized Self-Attention Module, which computes multidimensional attention through nonnegative matrix factorization, and integrate it into FactorizePhys, a proposed 3D-CNN model for robust rPPG signal extraction. | 21,624 | 2411.01542 | title_snapshot | [
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Multi-Group Proportional Representation in Retrieval | https://openreview.net/forum?id=BRZYhVHvSg | [
"Alex Oesterling",
"Claudio Mayrink Verdun",
"Alexander Glynn",
"Carol Xuan Long",
"Lucas Monteiro Paes",
"Sajani Vithana",
"Martina Cardone",
"Flavio Calmon"
] | Poster | fairness | Image search and retrieval tasks can perpetuate harmful stereotypes, erase cultural identities, and amplify social disparities. Current approaches to mitigate these representational harms balance the number of retrieved items across population groups defined by a small number of (often binary) attributes. However, most... | [
"Fairness",
"Proportional Representation",
"Multi-Group Fairness"
] | We introduce a novel metric for ensuring multi-group proportional representation over sets of images. We apply this metric to retrieval and propose an algorithm that maximizes similarity under a multi-group proportional representation constraint. | 21,620 | 2407.08571 | title_snapshot | [
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NeuralSteiner: Learning Steiner Tree for Overflow-avoiding Global Routing in Chip Design | https://openreview.net/forum?id=oEKFPSOWpp | [
"Ruizhi Liu",
"ZhishengZeng",
"Shizhe Ding",
"Jingyan Sui",
"Xingquan Li",
"Dongbo Bu"
] | Poster | machine_learning_for_other_sciences_and_fields | Global routing plays a critical role in modern chip design. The routing paths generated by global routers often form a rectilinear Steiner tree (RST). Recent advances from the machine learning community have shown the power of learning-based route generation; however, the yielded routing paths by the existing approache... | [
"Global routing",
"chip design",
"neural network",
"Steiner tree",
"deep learning",
"congestion"
] | We propose NeuralSteiner, a learning-based method to optimize overflow and wirelength simultaneously for global routing problem in chip design. | 21,619 | null | null | [
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The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations | https://openreview.net/forum?id=eHzIwAhj06 | [
"Tyler LaBonte",
"John Collins Hill",
"Xinchen zhang",
"Vidya Muthukumar",
"Abhishek Kumar"
] | Poster | fairness | Modern machine learning models are prone to over-reliance on spurious correlations, which can often lead to poor performance on minority groups. In this paper, we identify surprising and nuanced behavior of finetuned models on worst-group accuracy via comprehensive experiments on four well-established benchmarks across... | [
"spurious correlations",
"group robustness",
"distribution shift",
"class balancing"
] | We identify surprising and nuanced behavior of finetuned models on worst-group accuracy in settings including class-balancing, model scaling, and spectral analysis. | 21,606 | 2407.13957 | title_snapshot | [
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0.002152385888621211,
-0.07154297083616257,
0.010... |
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