Wojciech Szpankowski
16 papers · 2020–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (8) π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (11) π Interdisciplinary Bridge π Academic Marathon (5)
π
Cross-Pollinator
(12)
π
Renaissance Researcher
(5)
π
Interdisciplinary Bridge
π
Grand Slam
π
Keyword Champion
(2)
π
Century Club
(15)
ποΈ
Keyword Collector
(82)
π₯
Unstoppable
(6)
Conferences
AISTATS (4)
ALT (3)
COLT (2)
ICML (2)
NIPS (2)
AAAI (1)
ICLR (1)
JMLR (1)
Top co-authors
Research topics
Keywords
online learning
(6)
information theory
(5)
statistical learning
(3)
minimax regret
(3)
fourier expansion
(2)
logistic regression
(2)
phase transition
(2)
vc dimension
(2)
community detection
(1)
quantum machine learning
(1)
feature selection
(1)
fourier analysis
(1)
quantum computing
(1)
computational complexity
(1)
universal consistency
(1)
pac learning
(1)
message passing
(1)
regret minimization
(1)
online classification
(1)
minimax optimality
(1)
Papers
Phase Transition of Regret for Logistic Regression with Large Weights
ALT 2026
No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models
ICLR 2025
Online Distribution Learning with Local Privacy Constraints
AISTATS 2024
Information-theoretic Limits of Online Classification with Noisy Labels
NIPS 2024
Oracle-Efficient Hybrid Online Learning with Unknown Distribution
COLT 2024
Learning Functional Distributions with Private Labels
ICML 2023
Learning k-qubit Quantum Operators via Pauli Decomposition
AISTATS 2023
Agnostic PAC Learning of $k$-juntas Using $L_2$-Polynomial Regression
AISTATS 2023
Online Learning in Dynamically Changing Environments
COLT 2023
Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm
NIPS 2022
Toward Physically Realizable Quantum Neural Networks
AAAI 2022
Statistical and computational thresholds for the planted k-densest sub-hypergraph problem
AISTATS 2022
Data-Derived Weak Universal Consistency
JMLR 2022
Precise Minimax Regret for Logistic Regression with Categorical Feature Values
ALT 2021
Finding Relevant Information via a Discrete Fourier Expansion
ICML 2021
Toward universal testing of dynamic network models
ALT 2020