Karan Singh

26 papers · 2017–2025 · 7 conferences · across top CS/AI conferences

Achievements

🏃 Academic Marathon (8) 🗺️ Taxonomy Completionist (42) 🌈 Renaissance Researcher (7) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (14) 🌍 Conference Polyglot (7) 🤝 Dynamic Duo (14) 🌱 Topic Pioneer 💎 Century Club (26) 🗃️ Keyword Collector (107) ⚡ Prolific Year (5) 📈 Trend Setter ❓ The Questioner 🔥 Unstoppable (9)

Conferences

ICML (10) NIPS (6) COLT (3) CVPR (3) ALT (2) ACL (1) L4DC (1)

Top co-authors

Elad Hazan (14) Naman Agarwal (9) Cyril Zhang (5) Udaya Ghai (4) Yi Zhang (3) Sham Kakade (3) Brian Bullins (3) Holden Lee (2) Niloy J. Mitra (2) Satyen Kale (2)

Research topics

Differential Privacy (1)

Keywords

linear dynamical system (8) regret bound (8) online learning (4) regret minimization (4) online control (3) sample complexity (3) online gradient descent (2) reinforcement learning (2) local optimum (2) diffusion model (2) spectral filtering (2) boosting algorithm (2) depth estimation (2) non-stochastic control (2) differential privacy (2) empirical risk minimization (2) online convex optimization (2) markov decision process (2) adversarial perturbation (2) knowledge representation (1)

Papers

Sample-Optimal Agnostic Boosting with Unlabeled Data ICML 2025

Motion Modes: What Could Happen Next? CVPR 2025

Faster Global Minimum Cut with Predictions ICML 2025

Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements ICML 2024

Diffusion Handles Enabling 3D Edits for Diffusion Models by Lifting Activations to 3D CVPR 2024

Sample-Efficient Agnostic Boosting NIPS 2024

Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret L4DC 2023

Online Nonstochastic Model-Free Reinforcement Learning NIPS 2023

Evaluation Metrics for Depth and Flow of Knowledge in Non-fiction Narrative Texts ACL 2023

Variance-Reduced Conservative Policy Iteration ALT 2023

Differentially Private and Lazy Online Convex Optimization COLT 2023

A Boosting Approach to Reinforcement Learning NIPS 2022

Boosting for Online Convex Optimization ICML 2021

A Regret Minimization Approach to Iterative Learning Control ICML 2021

No-Regret Prediction in Marginally Stable Systems COLT 2020

The Nonstochastic Control Problem ALT 2020

Improper Learning for Non-Stochastic Control COLT 2020

Online Control with Adversarial Disturbances ICML 2019

Creative Flow+ Dataset CVPR 2019

Efficient Full-Matrix Adaptive Regularization ICML 2019

Provably Efficient Maximum Entropy Exploration ICML 2019

Logarithmic Regret for Online Control NIPS 2019

Spectral Filtering for General Linear Dynamical Systems NIPS 2018

Efficient Regret Minimization in Non-Convex Games ICML 2017

The Price of Differential Privacy for Online Learning ICML 2017

Learning Linear Dynamical Systems via Spectral Filtering NIPS 2017