Aleksandrs Slivkins
28 papers · 2009–2025 · 6 conferences · across top CS/AI conferences
Achievements
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πΊοΈ Taxonomy Completionist (15) π§ Keyword Pioneer π Interdisciplinary Bridge π Renaissance Researcher (6) π£ Hot Topic Early Bird
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Interdisciplinary Bridge
π£
Hot Topic Early Bird
π§
Keyword Pioneer
π
Keyword Trendsetter Combo
(3)
πΊ
Lone Wolf
(4)
π¬
Deep Specialist
(16)
π
Keyword Champion
(3)
π±
Topic Pioneer
π§¬
Topic Evolution
π
Trend Setter
β‘
Prolific Year
(5)
ποΈ
Keyword Collector
(105)
β
The Questioner
π
Century Club
(28)
π
Conference Pioneer
π₯
Unstoppable
(8)
Conferences
COLT (11)
NIPS (8)
JMLR (4)
AAAI (2)
ICML (2)
AISTATS (1)
Top co-authors
Research topics
Keywords
multi-armed bandit
(16)
regret bound
(12)
contextual bandit
(11)
online learning
(6)
online algorithm
(5)
knapsack problem
(3)
bandit algorithm
(3)
continuous action
(3)
packing constraint
(2)
regression oracle
(2)
vanishing regret
(2)
budget constraint
(2)
mechanism design
(2)
covering constraint
(2)
adaptive algorithm
(2)
metric space
(2)
combinatorial optimization
(2)
greedy algorithm
(2)
decision making
(2)
lagrangian approach
(2)
Papers
Robust Performance Incentivizing Algorithms for Multi-Armed Bandits with Strategic Agents
AAAI 2025
Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression
JMLR 2024
Can large language models explore in-context?
NIPS 2024
Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics
COLT 2024
Impact of Decentralized Learning on Player Utilities in Stackelberg Games
ICML 2024
Content Filtering with Inattentive Information Consumers
AAAI 2024
Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression
COLT 2023
Bandit Social Learning under Myopic Behavior
NIPS 2023
Incentivizing Combinatorial Bandit Exploration
NIPS 2022
Bandits with Knapsacks beyond the Worst Case
NIPS 2021
Efficient Contextual Bandits with Continuous Actions
NIPS 2020
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting
JMLR 2020
Constrained episodic reinforcement learning in concave-convex and knapsack settings
NIPS 2020
Contextual bandits with continuous actions: Smoothing, zooming, and adapting
COLT 2019
Combinatorial Semi-Bandits with Knapsacks
AISTATS 2018
The Externalities of Exploration and How Data Diversity Helps Exploitation
COLT 2018
Contextual Dueling Bandits
COLT 2015
Resourceful Contextual Bandits
COLT 2014
Robust Multi-objective Learning with Mentor Feedback
COLT 2014
One Practical Algorithm for Both Stochastic and Adversarial Bandits
ICML 2014
Contextual Bandits with Similarity Information
JMLR 2014
Adaptive Crowdsourcing Algorithms for the Bandit Survey Problem
COLT 2013
Ranked Bandits in Metric Spaces: Learning Diverse Rankings over Large Document Collections
JMLR 2013
The Best of Both Worlds: Stochastic and Adversarial Bandits
COLT 2012
Multi-armed bandits on implicit metric spaces
NIPS 2011
Monotone multi-armed bandit allocations
COLT 2011
Contextual Bandits with Similarity Information
COLT 2011
Adapting to the Shifting Intent of Search Queries
NIPS 2009