← Authors

Zheng Wen

39 papers · 2013–2023 · 9 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (10) 🌈 Renaissance Researcher (8) 🌍 Conference Polyglot (9) 🐝 Cross-Pollinator (11) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (15) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🀝 Dynamic Duo (18) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (11) πŸ† Keyword Champion (3) πŸš€ Conference Pioneer ⚑ Prolific Year (8) πŸ—ƒοΈ Keyword Collector (136) πŸ“ˆ Trend Setter πŸ’Ž Century Club (39) πŸ”₯ Unstoppable (9)

Conferences

ICML (13) NIPS (10) AISTATS (6) UAI (3) ICLR (2) IJCAI (2) AAAI (1) ACL (1) JMLR (1)

Top co-authors

Branislav Kveton (18) Benjamin Van Roy (11) Csaba SzepesvΓ‘ri (8) Ian Osband (7) Xiuyuan Lu (6) Azin Ashkan (5) Vikranth Dwaracherla (5) Morteza Ibrahimi (5) Seyed Mohammad Asghari (4) Ruiyi Zhang (4)

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