Cover Image

Scaling the Convex Barrier with Sparse Dual Algorithms

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	De Palma, Alessandro, Behl, Harkirat Singh, Bunel, Rudy, Torr, Philip H. S., Kumar, M. Pawan
Format:	Preprint
Published:	2021
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Expressive Losses for Verified Robustness via Convex Combinations
by: De Palma, Alessandro, et al.
Published: (2023)

Verified Neural Compressed Sensing
by: Bunel, Rudy, et al.
Published: (2024)

Branch and Bound for Piecewise Linear Neural Network Verification
by: Bunel, Rudy, et al.
Published: (2019)

Efficient Error Certification for Physics-Informed Neural Networks
by: Eiras, Francisco, et al.
Published: (2023)

PEEKABOO: Interactive Video Generation via Masked-Diffusion
by: Jain, Yash, et al.
Published: (2023)

AI Scientist via Synthetic Task Scaling
by: Cai, Ziyang, et al.
Published: (2026)

Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models
by: Eiras, Francisco, et al.
Published: (2024)

Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
by: Shrivastava, Vaishnavi, et al.
Published: (2025)

Hierarchical Sparse Plus Low Rank Compression of LLM
by: Kumar, Pawan, et al.
Published: (2025)

Do Sparse Autoencoders Generalize? A Case Study of Answerability
by: Heindrich, Lovis, et al.
Published: (2025)

Learning Better Certified Models from Empirically-Robust Teachers
by: De Palma, Alessandro
Published: (2026)

SAGE: Scalable Ground Truth Evaluations for Large Sparse Autoencoders
by: Venhoff, Constantin, et al.
Published: (2024)

Quantum Algorithms for Projection-Free Sparse Convex Optimization
by: He, Jianhao, et al.
Published: (2025)

Sparse Convex Biclustering
by: Jiang, Jiakun, et al.
Published: (2026)

Dual Adaptivity: Universal Algorithms for Minimizing the Adaptive Regret of Convex Functions
by: Zhang, Lijun, et al.
Published: (2025)

Improving Semantic Uncertainty Quantification in Language Model Question-Answering via Token-Level Temperature Scaling
by: Lamb, Tom A., et al.
Published: (2026)

Shuffling Momentum Gradient Algorithm for Convex Optimization
by: Tran, Trang H., et al.
Published: (2024)

When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations
by: Petrov, Aleksandar, et al.
Published: (2023)

Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation
by: Zhang, Wenxuan, et al.
Published: (2024)

Oja's Algorithm for Streaming Sparse PCA
by: Kumar, Syamantak, et al.
Published: (2024)

Efficient Convex Algorithms for Universal Kernel Learning
by: Talitckii, Aleksandr, et al.
Published: (2023)

Energy Scale Degradation in Sparse Quantum Solvers: A Barrier to Quantum Utility
by: Dinh, Thang N., et al.
Published: (2025)

CRASH: Challenging Reinforcement-Learning Based Adversarial Scenarios For Safety Hardening
by: Kulkarni, Amar, et al.
Published: (2024)

Quantifying Feature Space Universality Across Large Language Models via Sparse Autoencoders
by: Lan, Michael, et al.
Published: (2024)

Online Learning on Hidden-Convex Losses via Algorithmic Equivalence: Optimal Regret, Geometric Barrier, and Bandit Feedback
by: Barakat, Anas, et al.
Published: (2026)

Prompting a Pretrained Transformer Can Be a Universal Approximator
by: Petrov, Aleksandar, et al.
Published: (2024)

First-Order Sparse Convex Optimization: Better Rates with Sparse Updates
by: Garber, Dan
Published: (2025)

Towards Certification of Uncertainty Calibration under Adversarial Attacks
by: Emde, Cornelius, et al.
Published: (2024)

Faster Verified Explanations for Neural Networks
by: De Palma, Alessandro, et al.
Published: (2025)

Decentralized Smoothing ADMM for Quantile Regression with Non-Convex Sparse Penalties
by: Mirzaeifard, Reza, et al.
Published: (2024)

Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation
by: Wei, Hui, et al.
Published: (2024)

Optimal and Efficient Algorithms for Decentralized Online Convex Optimization
by: Wan, Yuanyu, et al.
Published: (2024)

An Asymptotically Optimal Algorithm for the Convex Hull Membership Problem
by: Qiao, Gang, et al.
Published: (2023)

Towards Interpretable Sequence Continuation: Analyzing Shared Circuits in Large Language Models
by: Lan, Michael, et al.
Published: (2023)

Projection-free Algorithms for Online Convex Optimization with Adversarial Constraints
by: Sarkar, Dhruv, et al.
Published: (2025)

Optimal Anytime Algorithms for Online Convex Optimization with Adversarial Constraints
by: Sarkar, Dhruv, et al.
Published: (2025)

Naive Feature Selection: a Nearly Tight Convex Relaxation for Sparse Naive Bayes
by: Askari, Armin, et al.
Published: (2019)

Bi-Factorial Preference Optimization: Balancing Safety-Helpfulness in Language Models
by: Zhang, Wenxuan, et al.
Published: (2024)

Beyond Linear Probes: Dynamic Safety Monitoring for Language Models
by: Oldfield, James, et al.
Published: (2025)

Too Late to Recall: Explaining the Two-Hop Problem in Multimodal Knowledge Retrieval
by: Venhoff, Constantin, et al.
Published: (2025)