Cover Image

Learning with Exact Invariances in Polynomial Time

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Soleymani, Ashkan, Tahmasebi, Behrooz, Jegelka, Stefanie, Jaillet, Patrick
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Universal Class of Sharpness-Aware Minimization Algorithms
by: Tahmasebi, Behrooz, et al.
Published: (2024)

The Exact Sample Complexity Gain from Invariances for Kernel Regression
by: Tahmasebi, Behrooz, et al.
Published: (2023)

Sample Complexity Bounds for Estimating Probability Divergences under Invariances
by: Tahmasebi, Behrooz, et al.
Published: (2023)

Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry
by: Tahmasebi, Behrooz, et al.
Published: (2025)

Geometric Algorithms for Neural Combinatorial Optimization with Constraints
by: Karalias, Nikolaos, et al.
Published: (2025)

Counting Substructures with Higher-Order Graph Neural Networks: Possibility and Impossibility Results
by: Tahmasebi, Behrooz, et al.
Published: (2020)

Learning Linear Attention in Polynomial Time
by: Yau, Morris, et al.
Published: (2024)

Double Machine Learning Based Structure Identification from Temporal Data
by: Angelis, Emmanouil, et al.
Published: (2023)

LANPO: Bootstrapping Language and Numerical Feedback for Reinforcement Learning in LLMs
by: Li, Ang, et al.
Published: (2025)

G1: Teaching LLMs to Reason on Graphs with Reinforcement Learning
by: Guo, Xiaojun, et al.
Published: (2025)

Bridging Reasoning to Learning: Unmasking Illusions using Complexity Out of Distribution Generalization
by: Paqaleh, Mohammad Mahdi Samiei, et al.
Published: (2025)

Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
by: Gatmiry, Khashayar, et al.
Published: (2024)

Survey on Generalization Theory for Graph Neural Networks
by: Vasileiou, Antonis, et al.
Published: (2025)

How to Craft Backdoors with Unlabeled Data Alone?
by: Wang, Yifei, et al.
Published: (2024)

Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
by: Sim, Rachael Hwee Ling, et al.
Published: (2026)

The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
by: Lim, Derek, et al.
Published: (2024)

Fairness Aware Reward Optimization
by: Choi, Ching Lam, et al.
Published: (2026)

Continuous Invariance Learning
by: Lin, Yong, et al.
Published: (2023)

Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
by: Verma, Arun, et al.
Published: (2024)

On the Stability of Expressive Positional Encodings for Graphs
by: Huang, Yinan, et al.
Published: (2023)

Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
by: Zhang, Qi, et al.
Published: (2024)

Scaling Attention via Feature Sparsity
by: Xie, Yan, et al.
Published: (2026)

Operator-Guided Invariance Learning for Continuous Reinforcement Learning
by: Zhang, Zuyuan, et al.
Published: (2026)

Prompt Optimization with Human Feedback
by: Lin, Xiaoqiang, et al.
Published: (2024)

Learning Action-based Representations Using Invariance
by: Rudolph, Max, et al.
Published: (2024)

Generalized Attention Flow: Feature Attribution for Transformer Models via Maximum Flow
by: Azarkhalili, Behrooz, et al.
Published: (2025)

ReasonCACHE: Teaching LLMs To Reason Without Weight Updates
by: Gupta, Sharut, et al.
Published: (2026)

Online Scheduling for LLM Inference with KV Cache Constraints
by: Jaillet, Patrick, et al.
Published: (2025)

When More is Less: Understanding Chain-of-Thought Length in LLMs
by: Wu, Yuyang, et al.
Published: (2025)

No More K-means: Single-Stage Sparse Coding for Efficient Multi-Vector Retrieval
by: Guo, Lixuan, et al.
Published: (2026)

An adaptive sampling algorithm for data-generation to build a data-manifold for physical problem surrogate modeling
by: Mang, Chetra, et al.
Published: (2025)

CliquePH: Higher-Order Information for Graph Neural Networks through Persistent Homology on Clique Graphs
by: Buffelli, Davide, et al.
Published: (2024)

Learning Diffusion Models with Flexible Representation Guidance
by: Wang, Chenyu, et al.
Published: (2025)

Causal Graph Learning via Distributional Invariance of Cause-Effect Relationship
by: Nguyen, Nang Hung, et al.
Published: (2026)

Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
by: Deng, Chenhui, et al.
Published: (2024)

Causal Invariance and Counterfactual Learning Driven Cooperative Game for Multi-Label Classification
by: Fan, Yijia, et al.
Published: (2025)

An Information Criterion for Controlled Disentanglement of Multimodal Data
by: Wang, Chenyu, et al.
Published: (2024)

SUSD: Structured Unsupervised Skill Discovery through State Factorization
by: Hosseini, Seyed Mohammad Hadi, et al.
Published: (2026)

Understanding the Role of Equivariance in Self-supervised Learning
by: Wang, Yifei, et al.
Published: (2024)

Causal Discovery from Time-Series Data with Short-Term Invariance-Based Convolutional Neural Networks
by: Shen, Rujia, et al.
Published: (2024)