Matthias Grossglauser
21 papers · 2015–2026 · 9 conferences · across top CS/AI conferences
Achievements
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π Cross-Pollinator (6) π§ Keyword Pioneer π Academic Marathon (10) π Conference Polyglot (8) π Renaissance Researcher (8)
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Taxonomy Completionist
(40)
π§
Keyword Pioneer
π
Conference Polyglot
(8)
π
Keyword Champion
π
Trend Setter
π
Century Club
(19)
β‘
Prolific Year
(6)
ποΈ
Keyword Collector
(77)
Conferences
ICML (7)
NIPS (4)
UAI (3)
ALT (2)
ACML (1)
AISTATS (1)
COLT (1)
EACL (1)
NAACL (1)
Top co-authors
Keywords
pairwise comparison
(4)
bayesian inference
(3)
causal structure
(2)
multivariate hawkes process
(2)
preference learning
(2)
variational inference
(2)
recommender system
(2)
point process
(2)
event sequence
(2)
maximum likelihood estimation
(2)
query complexity
(2)
network analysis
(1)
maximum likelihood
(1)
bregman divergence
(1)
posterior distribution
(1)
information retrieval
(1)
markov chain monte carlo
(1)
community detection
(1)
collaborative filtering
(1)
stochastic process
(1)
Papers
Recycling History: Efficient Recommendations from Contextual Dueling Bandits
ALT 2026
Ranking Items from Discrete Ratings: The Cost of Unknown User Thresholds
ALT 2026
Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization
ICML 2025
Efficiently Escaping Saddle Points for Policy Optimization
UAI 2025
Measuring IIA Violations in Similarity Choices with Bayesian Models
UAI 2025
Hierarchical Reinforcement Learning with Targeted Causal Interventions
ICML 2025
Itβs All Relative: Learning Interpretable Models for Scoring Subjective Bias in Documents from Pairwise Comparisons
EACL 2024
Fast Interactive Search under a Scale-Free Comparison Oracle
UAI 2024
Why the Metric Backbone Preserves Community Structure
NIPS 2024
Causal Effect Identification in a Sub-Population with Latent Variables
NIPS 2024
Universal Lower Bounds and Optimal Rates: Achieving Minimax Clustering Error in Sub-Exponential Mixture Models
COLT 2024
Discovering Lobby-Parliamentarian Alignments through NLP
NAACL 2024
Cumulants of Hawkes Processes are Robust to Observation Noise
ICML 2021
A Variational Inference Approach to Learning Multivariate Wold Processes
AISTATS 2021
Scalable and Efficient Comparison-based Search without Features
ICML 2020
Learning Hawkes Processes Under Synchronization Noise
ICML 2019
Learning Hawkes Processes from a handful of events
NIPS 2019
ChoiceRank: Identifying Preferences from Node Traffic in Networks
ICML 2017
Just Sort It! A Simple and Effective Approach to Active Preference Learning
ICML 2017
Collaborative Recurrent Neural Networks for Dynamic Recommender Systems
ACML 2016
Fast and Accurate Inference of PlackettβLuce Models
NIPS 2015