Saved in:
| Main Authors: | Das, Santanu, Batra, Jatin, Srivastava, Piyush |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2405.16639 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Tractable Gaussian Phase Retrieval with Heavy Tails and Adversarial Corruption with Near-Linear Sample Complexity
by: Das, Santanu, et al.
Published: (2026)
by: Das, Santanu, et al.
Published: (2026)
Convex Basins in Single-Index Model Loss Landscapes: Applications to Robust Recovery under Strong Adversarial Corruption
by: Das, Santanu, et al.
Published: (2026)
by: Das, Santanu, et al.
Published: (2026)
Calibeating for general proper losses: A Bregman divergence approach
by: Fichtl, Maximilian, et al.
Published: (2026)
by: Fichtl, Maximilian, et al.
Published: (2026)
Symplectic Bregman divergences
by: Nielsen, Frank
Published: (2024)
by: Nielsen, Frank
Published: (2024)
Curved representational Bregman divergences and their applications
by: Nielsen, Frank
Published: (2025)
by: Nielsen, Frank
Published: (2025)
Bias-variance decompositions: the exclusive privilege of Bregman divergences
by: Heskes, Tom
Published: (2025)
by: Heskes, Tom
Published: (2025)
Innovation: An Almost Characterization of Hallucination
by: Das, Nishant P., et al.
Published: (2026)
by: Das, Nishant P., et al.
Published: (2026)
Comparing skill of historical rainfall data based monsoon rainfall prediction in India with NWP forecasts
by: Narula, Apoorva, et al.
Published: (2024)
by: Narula, Apoorva, et al.
Published: (2024)
Generalising maximum mean discrepancy: kernelised functional Bregman divergences
by: Tsuchida, Russell, et al.
Published: (2026)
by: Tsuchida, Russell, et al.
Published: (2026)
Bregman-Hausdorff divergence: strengthening the connections between computational geometry and machine learning
by: Pham, Tuyen, et al.
Published: (2025)
by: Pham, Tuyen, et al.
Published: (2025)
A unifying Bayesian framework for adversarial robustness
by: Arce, Pablo G., et al.
Published: (2025)
by: Arce, Pablo G., et al.
Published: (2025)
A unified framework for evaluating the robustness of machine-learning interpretability for prospect risking
by: Chowdhury, Prithwijit, et al.
Published: (2026)
by: Chowdhury, Prithwijit, et al.
Published: (2026)
Approximating the Total Variation Distance between Gaussians
by: Bhattacharyya, Arnab, et al.
Published: (2025)
by: Bhattacharyya, Arnab, et al.
Published: (2025)
ASRL:A robust loss function with potential for development
by: Hui, Chenyu, et al.
Published: (2025)
by: Hui, Chenyu, et al.
Published: (2025)
Alpha-divergence loss function for neural density ratio estimation
by: Kitazawa, Yoshiaki
Published: (2024)
by: Kitazawa, Yoshiaki
Published: (2024)
Superposition unifies power-law training dynamics
by: Chen, Zixin Jessie, et al.
Published: (2026)
by: Chen, Zixin Jessie, et al.
Published: (2026)
Minimizing robust density power-based divergences for general parametric density models
by: Okuno, Akifumi
Published: (2023)
by: Okuno, Akifumi
Published: (2023)
rECGnition_v1.0: Arrhythmia detection using cardiologist-inspired multi-modal architecture incorporating demographic attributes in ECG
by: Srivastava, Shreya, et al.
Published: (2024)
by: Srivastava, Shreya, et al.
Published: (2024)
FGM optimization in complex domains using Gaussian process regression based profile generation algorithm
by: Konda, Chaitanya Kumar, et al.
Published: (2025)
by: Konda, Chaitanya Kumar, et al.
Published: (2025)
Governance-as-a-Service: A Multi-Agent Framework for AI System Compliance and Policy Enforcement
by: Gaurav, Suyash, et al.
Published: (2025)
by: Gaurav, Suyash, et al.
Published: (2025)
A Generalized Bias-Variance Decomposition for Bregman Divergences
by: Pfau, David
Published: (2025)
by: Pfau, David
Published: (2025)
Bounds on Lp errors in density ratio estimation via f-divergence loss functions
by: Kitazawa, Yoshiaki
Published: (2024)
by: Kitazawa, Yoshiaki
Published: (2024)
Rethinking Bregman Divergences in Kronecker-Factored Optimizers
by: Liu, Bing, et al.
Published: (2026)
by: Liu, Bing, et al.
Published: (2026)
Stream separation improves Bregman conditioning in transformers
by: Kerce, James Clayton
Published: (2026)
by: Kerce, James Clayton
Published: (2026)
Provably robust learning of regression neural networks using $β$-divergences
by: Ghosh, Abhik, et al.
Published: (2026)
by: Ghosh, Abhik, et al.
Published: (2026)
Bregman Douglas-Rachford Splitting Method
by: Ma, Shiqian, et al.
Published: (2025)
by: Ma, Shiqian, et al.
Published: (2025)
Evaluating Brain-Inspired Modular Training in Automated Circuit Discovery for Mechanistic Interpretability
by: Nainani, Jatin
Published: (2024)
by: Nainani, Jatin
Published: (2024)
Adaptive Regularization for Sparsity Control in Bregman-Based Optimizers
by: Aloradi, Ahmad, et al.
Published: (2026)
by: Aloradi, Ahmad, et al.
Published: (2026)
EVCL: Elastic Variational Continual Learning with Weight Consolidation
by: Batra, Hunar, et al.
Published: (2024)
by: Batra, Hunar, et al.
Published: (2024)
What Can You Do When You Have Zero Rewards During RL?
by: Prakash, Jatin, et al.
Published: (2025)
by: Prakash, Jatin, et al.
Published: (2025)
GL-TSVM: A robust and smooth twin support vector machine with guardian loss function
by: Akhtar, Mushir, et al.
Published: (2024)
by: Akhtar, Mushir, et al.
Published: (2024)
Online Nonconvex Bilevel Optimization with Bregman Divergences
by: Bohne, Jason, et al.
Published: (2024)
by: Bohne, Jason, et al.
Published: (2024)
Multilingual-To-Multimodal (M2M): Unlocking New Languages with Monolingual Text
by: Pasi, Piyush Singh
Published: (2026)
by: Pasi, Piyush Singh
Published: (2026)
Geometric Convergence Analysis of Variational Inference via Bregman Divergences
by: Bohara, Sushil, et al.
Published: (2025)
by: Bohara, Sushil, et al.
Published: (2025)
Regularizing cross entropy loss via minimum entropy and K-L divergence
by: Ibraheem, Abdulrahman Oladipupo
Published: (2025)
by: Ibraheem, Abdulrahman Oladipupo
Published: (2025)
A Bregman firmly nonexpansive proximal operator for baryconvex optimization
by: Achab, Mastane
Published: (2024)
by: Achab, Mastane
Published: (2024)
Attention and Compression is all you need for Controllably Efficient Language Models
by: Prakash, Jatin, et al.
Published: (2025)
by: Prakash, Jatin, et al.
Published: (2025)
Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M
by: Pant, Piyush
Published: (2025)
by: Pant, Piyush
Published: (2025)
Lower Difficulty and Better Robustness: A Bregman Divergence Perspective for Adversarial Training
by: Wu, Zihui, et al.
Published: (2022)
by: Wu, Zihui, et al.
Published: (2022)
Robust Sublinear Convergence Rates for Iterative Bregman Projections
by: Peyré, Gabriel
Published: (2026)
by: Peyré, Gabriel
Published: (2026)
Similar Items
-
Tractable Gaussian Phase Retrieval with Heavy Tails and Adversarial Corruption with Near-Linear Sample Complexity
by: Das, Santanu, et al.
Published: (2026) -
Convex Basins in Single-Index Model Loss Landscapes: Applications to Robust Recovery under Strong Adversarial Corruption
by: Das, Santanu, et al.
Published: (2026) -
Calibeating for general proper losses: A Bregman divergence approach
by: Fichtl, Maximilian, et al.
Published: (2026) -
Symplectic Bregman divergences
by: Nielsen, Frank
Published: (2024) -
Curved representational Bregman divergences and their applications
by: Nielsen, Frank
Published: (2025)