Yanjun Han
Assistant Professor of Mathematics and Data Science
Studies statistics and learning theory, including online learning and bandits and information-theoretic limits.
Yanjun Han's lab at NYU works on learning theory & optimization, reinforcement learning and data management & big data. 21 papers since 2023, 16 at top venues, mostly COLT and NeurIPS. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 76%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 7 papers2026 · T1 7 · collecting
- 3 papers2025 · T1 2
- 7 papers2024 · T1 4
- 4 papers2023 · T1 3
T1 venuesOtherVenues: COLT, NeurIPS, ICLR, ICML, AISTATS
Research focuspaper titles that use each topic's words
- Reinforcement learning5 papers
- Learning theory & optimization3 papers
- information-theoretic1 paper
- Data management & big data0 papers
- limits0 papers
Paper list
From the lab homepage.
20267 papers
- COLT (T1)An Empirical Bayesian Perspective on Heteroskedastic Mean Estimation (opens in a new tab)
- ICLR (T1)Interactive Learning of Single-Index Models via Stochastic Gradient Descent (opens in a new tab)
- AISTATS (T1)Optimal Arm Elimination Algorithms for Combinatorial Bandits (opens in a new tab)
- ICML (T1)PETS: A Principled Framework Towards Optimal Trajectory Allocation for Efficient Test-Time Self-Consistency (opens in a new tab)
- ICLR (T1)Semi-Parametric Contextual Pricing with General Smoothness (opens in a new tab)
- ICML (T1)The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions (opens in a new tab)
- COLT (T1)Universal priors: solving empirical Bayes via Bayesian inference and pretraining (opens in a new tab)
20253 papers
- SIAM Journal on Mathematics of Data ScienceCovariance alignment: from maximum likelihood estimation to Gromov--Wasserstein (opens in a new tab)
- NeurIPS (T1)Evolution of Information in Interactive Decision Making: A Case Study for Multi-Armed Bandits (opens in a new tab)
- Operations Research (T1)Optimal No-regret Learning in Repeated First-price Auctions (opens in a new tab)
20247 papers
- NeurIPS (T1)Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability (opens in a new tab)
- RANDOMOn the amortized complexity of approximate counting (opens in a new tab)
- The Annals of StatisticsOn the Statistical Complexity of Sample Amplification (opens in a new tab)
- NeurIPS (T1)Online Estimation via Offline Estimation: An Information-Theoretic Framework (opens in a new tab)
- COLT (T1)Prediction from compression for models with infinite memory, with applications to hidden Markov and renewal processes (opens in a new tab)
- The Annals of StatisticsStatistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits (opens in a new tab)
- NeurIPS (T1)Stochastic contextual bandits with graph feedback: from independence number to MAS number (opens in a new tab)
20234 papers
- COLT (T1)Minimax Optimal Testing by Classification (opens in a new tab)
- NeurIPS (T1)Online Learning in Multi-unit Auctions (opens in a new tab)
- IEEE Transactions on Information TheoryOptimal prediction of Markov chains with and without spectral gap (opens in a new tab)
- COLT (T1)Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to NYUFall 2027
Computer Science PhD (Courant / Tandon)
- Round
- Single round (December)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Data
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- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
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