Zheng Wen
39 papers · 2013–2023 · 9 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (15) π Interdisciplinary Bridge π Conference Polyglot (9)
πΊοΈ
Taxonomy Completionist
(15)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π€
Dynamic Duo
(18)
π
Triple Crown
π
Grand Slam
π¬
Deep Specialist
(11)
π
Keyword Champion
(3)
π
Conference Pioneer
β‘
Prolific Year
(8)
ποΈ
Keyword Collector
(136)
π
Trend Setter
π
Century Club
(39)
π₯
Unstoppable
(9)
Conferences
ICML (13)
NIPS (10)
AISTATS (6)
UAI (3)
ICLR (2)
IJCAI (2)
AAAI (1)
ACL (1)
JMLR (1)
Top co-authors
Keywords
regret bound
(21)
multi-armed bandit
(13)
online learning
(13)
thompson sampling
(6)
reinforcement learning
(4)
learning to rank
(4)
combinatorial optimization
(3)
click model
(3)
stochastic optimization
(3)
influence maximization
(3)
ucb algorithm
(3)
joint prediction
(3)
posterior distribution
(3)
submodular optimization
(3)
cascade model
(3)
bayesian inference
(2)
linear bandit
(2)
bandit algorithm
(2)
social network
(2)
combinatorial semi-bandit
(2)
Papers
Epistemic Neural Networks
NIPS 2023
Approximate Thompson Sampling via Epistemic Neural Networks
UAI 2023
Leveraging Demonstrations to Improve Online Learning: Quality Matters
ICML 2023
Neural Contextual Bandits with Deep Representation and Shallow Exploration
ICLR 2022
The Neural Testbed: Evaluating Joint Predictions
NIPS 2022
An Analysis of Ensemble Sampling
NIPS 2022
Evaluating high-order predictive distributions in deep learning
UAI 2022
Joint Online Learning and Decision-making via Dual Mirror Descent
ICML 2021
Nested-Wasserstein Self-Imitation Learning for Sequence Generation
AISTATS 2020
Hypermodels for Exploration
ICLR 2020
Structured Policy Iteration for Linear Quadratic Regulator
ICML 2020
Stochastic Online Learning with Probabilistic Graph Feedback
AAAI 2020
Graphical Models Meet Bandits: A Variational Thompson Sampling Approach
ICML 2020
Budgeted Online Influence Maximization
ICML 2020
On Efficiency in Hierarchical Reinforcement Learning
NIPS 2020
Improving Adversarial Text Generation by Modeling the Distant Future
ACL 2020
Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank
UAI 2019
Scalable Thompson Sampling via Optimal Transport
AISTATS 2019
Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Bandit
AISTATS 2019
Conservative Exploration using Interleaving
AISTATS 2019
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits
ICML 2019
Deep Exploration via Randomized Value Functions
JMLR 2019
Bootstrapping Upper Confidence Bound
NIPS 2019
Scalar Posterior Sampling with Applications
NIPS 2018
Stochastic Rank-1 Bandits
AISTATS 2017
Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback
NIPS 2017
Model-Independent Online Learning for Influence Maximization
ICML 2017
Online Learning to Rank in Stochastic Click Models
ICML 2017
Bernoulli Rank-1 Bandits for Click Feedback
IJCAI 2017
DCM Bandits: Learning to Rank with Multiple Clicks
ICML 2016
Generalization and Exploration via Randomized Value Functions
ICML 2016
Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits
AISTATS 2015
Combinatorial Cascading Bandits
NIPS 2015
Optimal Greedy Diversity for Recommendation
IJCAI 2015
Cascading Bandits: Learning to Rank in the Cascade Model
ICML 2015
Efficient Learning in Large-Scale Combinatorial Semi-Bandits
ICML 2015
Sequential Bayesian Search
ICML 2013
Efficient Exploration and Value Function Generalization in Deterministic Systems
NIPS 2013
Adaptive Submodular Maximization in Bandit Setting
NIPS 2013