Cover Image

A Spectral View of Adversarially Robust Features

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Garg, Shivam, Sharan, Vatsal, Zhang, Brian Hu, Valiant, Gregory
Format:	Preprint
Published:	2018
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Sample Amplification: Increasing Dataset Size even when Learning is Impossible
by: Axelrod, Brian, et al.
Published: (2019)

On the Statistical Complexity of Sample Amplification
by: Axelrod, Brian, et al.
Published: (2022)

Discovering Data Structures: Nearest Neighbor Search and Beyond
by: Salemohamed, Omar, et al.
Published: (2024)

Efficient Convex Optimization Requires Superlinear Memory
by: Marsden, Annie, et al.
Published: (2022)

Testing with Non-identically Distributed Samples
by: Garg, Shivam, et al.
Published: (2023)

How Muon's Spectral Design Benefits Generalization: A Study on Imbalanced Data
by: Vasudeva, Bhavya, et al.
Published: (2025)

Limitations on Accurate, Trusted, Human-level Reasoning
by: Panigrahy, Rina, et al.
Published: (2025)

Pre-trained Large Language Models Use Fourier Features to Compute Addition
by: Zhou, Tianyi, et al.
Published: (2024)

Efficient Swap Multicalibration of Elicitable Properties
by: Hu, Lunjia, et al.
Published: (2025)

Improved Bounds for Swap Multicalibration and Swap Omniprediction
by: Luo, Haipeng, et al.
Published: (2025)

Optimal Multiclass U-Calibration Error and Beyond
by: Luo, Haipeng, et al.
Published: (2024)

Adaptive and oblivious statistical adversaries are equivalent
by: Blanc, Guy, et al.
Published: (2024)

Attainability of Two-Point Testing Rates for Finite-Sample Location Estimation
by: Compton, Spencer, et al.
Published: (2025)

On the Inherent Privacy of Zeroth Order Projected Gradient Descent
by: Gupta, Devansh, et al.
Published: (2025)

FoNE: Precise Single-Token Number Embeddings via Fourier Features
by: Zhou, Tianyi, et al.
Published: (2025)

Stability and Multigroup Fairness in Ranking with Uncertain Predictions
by: Devic, Siddartha, et al.
Published: (2024)

When is Multicalibration Post-Processing Necessary?
by: Hansen, Dutch, et al.
Published: (2024)

Transformers Provably Learn Algorithmic Solutions for Graph Connectivity, But Only with the Right Data
by: Ye, Qilin, et al.
Published: (2025)

On the Entropy Calibration of Language Models
by: Cao, Steven, et al.
Published: (2025)

Simultaneous Swap Regret Minimization via KL-Calibration
by: Luo, Haipeng, et al.
Published: (2025)

Auditability and the Landscape of Distance to Multicalibration
by: Derhake, Nathan, et al.
Published: (2025)

Feature Statistics with Uncertainty Help Adversarial Robustness
by: Wang, Ran, et al.
Published: (2025)

The Rich and the Simple: On the Implicit Bias of Adam and SGD
by: Vasudeva, Bhavya, et al.
Published: (2025)

Proper Learnability and the Role of Unlabeled Data
by: Asilis, Julian, et al.
Published: (2025)

Regularization and Optimal Multiclass Learning
by: Asilis, Julian, et al.
Published: (2023)

Understanding Contextual Recall in Transformers: How Finetuning Enables In-Context Reasoning over Pretraining Knowledge
by: Vasudeva, Bhavya, et al.
Published: (2026)

Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression
by: Fu, Deqing, et al.
Published: (2023)

Spectral Superposition: A Theory of Feature Geometry
by: Ivanov, Georgi, et al.
Published: (2026)

Depth Separations in Neural Networks: Separating the Dimension from the Accuracy
by: Safran, Itay, et al.
Published: (2024)

Online Distributionally Robust LLM Alignment via Regression to Relative Reward
by: Sahu, Sharan, et al.
Published: (2025)

Convergent Evolution: How Different Language Models Learn Similar Number Representations
by: Fu, Deqing, et al.
Published: (2026)

Adversarial Fair Multi-View Clustering
by: Jiang, Mudi, et al.
Published: (2025)

The Median is Easier than it Looks: Approximation with a Constant-Depth, Linear-Width ReLU Network
by: Dutta, Abhigyan, et al.
Published: (2026)

Transformers Learn Low Sensitivity Functions: Investigations and Implications
by: Vasudeva, Bhavya, et al.
Published: (2024)

A Graph-Enhanced Deep-Reinforcement Learning Framework for the Aircraft Landing Problem
by: Maru, Vatsal
Published: (2025)

Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization
by: Sun, Zexu, et al.
Published: (2023)

From Linear to Spline-Based Classification:Developing and Enhancing SMPA for Noisy Non-Linear Datasets
by: Srivastava, Vatsal
Published: (2025)

Latent Concept Disentanglement in Transformer-based Language Models
by: Hong, Guan Zhe, et al.
Published: (2025)

Understanding Adversarial Robustness from Feature Maps of Convolutional Layers
by: Xu, Cong, et al.
Published: (2022)

Cosine-Gated Adam-Decay: Drop-In Staleness-Aware Outer Optimization for Decoupled DiLoCo
by: Shah, Vatsal, et al.
Published: (2026)