Nicholas Bambos
14 papers · 2017–2024 · 4 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (7) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (4) 🐝 Cross-Pollinator (11)
🏃
Academic Marathon
(7)
🧭
Keyword Pioneer
🔥
Unstoppable
(8)
💎
Century Club
(14)
❓
The Questioner
📈
Trend Setter
🗃️
Keyword Collector
(76)
Conferences
NIPS (9)
ICML (3)
AISTATS (1)
JMLR (1)
Top co-authors
Keywords
game theory
(4)
distributed learning
(4)
multi-armed bandit
(4)
nash equilibrium
(4)
regret bound
(3)
zero-sum game
(3)
online algorithm
(3)
multi-agent learning
(2)
online learning
(2)
delayed feedback
(2)
adversarial bandit
(2)
gradient descent
(1)
kalman filter
(1)
regularized learning
(1)
non-convex optimization
(1)
stochastic gradient descent
(1)
accelerated gradient
(1)
online mirror descent
(1)
nash equilibria
(1)
convergence analysis
(1)
Papers
Accelerated Regularized Learning in Finite N-Person Games
NIPS 2024
Payoff-based Learning with Matrix Multiplicative Weights in Quantum Games
NIPS 2023
Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints
AISTATS 2023
No Weighted-Regret Learning in Adversarial Bandits with Delays
JMLR 2022
Queue Up Your Regrets: Achieving the Dynamic Capacity Region of Multiplayer Bandits
NIPS 2022
Online Learning for Load Balancing of Unknown Monotone Resource Allocation Games
ICML 2021
Distributed Distillation for On-Device Learning
NIPS 2020
My Fair Bandit: Distributed Learning of Max-Min Fairness with Multi-player Bandits
ICML 2020
Cooperative Multi-player Bandit Optimization
NIPS 2020
Online EXP3 Learning in Adversarial Bandits with Delayed Feedback
NIPS 2019
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go?
ICML 2018
Learning in Games with Lossy Feedback
NIPS 2018
Stochastic Mirror Descent in Variationally Coherent Optimization Problems
NIPS 2017
Countering Feedback Delays in Multi-Agent Learning
NIPS 2017