Krishna Pillutla
13 papers · 2021–2025 · 7 venues · across top CS/AI venues
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Research topics
Machine Learning
(12)
Optimization & Theory
(10)
Deep Learning
(6)
Artificial Intelligence
(4)
Application Areas
(4)
Core AI
(3)
Models
(3)
Mathematics & Optimization
(2)
Natural Language Processing
(2)
Applications
(2)
Learning Paradigms · Machine Learning
(2)
Learning Paradigms · Artificial Intelligence
(2)
Learning Types
(2)
Optimization
(2)
Architectures
(1)
Keywords
differential privacy
(3)
generative model
(2)
linear convergence
(2)
federated learning
(2)
text generation
(2)
large language model
(2)
privacy attack
(1)
image retrieval
(1)
representation learning
(1)
matrix factorization
(1)
non-convex optimization
(1)
attention mechanism
(1)
stochastic optimization
(1)
language modeling
(1)
distributed learning
(1)
image generation
(1)
sample complexity
(1)
distributed optimization
(1)
ai safety
(1)
convergence analysis
(1)
Papers
Language Models can Subtly Deceive Without Lying: A Case Study on Strategic Phrasing in Legislation
ACL 2025
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning
ICLR 2024
Distributionally Robust Optimization with Bias and Variance Reduction
ICLR 2024
User Inference Attacks on Large Language Models
EMNLP 2024
Influence Diagnostics under Self-concordance
AISTATS 2023
MAUVE Scores for Generative Models: Theory and Practice
JMLR 2023
Stochastic Optimization for Spectral Risk Measures
AISTATS 2023
Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning
NeurIPS 2023
Unleashing the Power of Randomization in Auditing Differentially Private ML
NeurIPS 2023
Federated Learning with Partial Model Personalization
ICML 2022
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals
NeurIPS 2021
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes
NeurIPS 2021
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers
NeurIPS 2021