Julian Katz-Samuels
19 papers · 2018–2026 · 9 venues · across top CS/AI venues
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Research topics
Machine Learning
(17)
Learning Types Β· Machine Learning
(14)
Optimization & Theory
(11)
Artificial Intelligence
(5)
Mathematics & Optimization
(5)
Core Methods
(5)
Optimization
(5)
Deep Learning
(4)
Natural Language Processing
(3)
Application Areas
(3)
Core AI
(3)
Learning Types Β· Deep Learning
(3)
Resources & Methods
(3)
Learning Paradigms
(2)
Models
(1)
Keywords
experimental design
(4)
sample complexity
(3)
direct preference optimization
(3)
linear bandit
(3)
pure exploration
(3)
multi-armed bandit
(3)
large language model
(2)
empirical process
(2)
version space
(2)
best arm identification
(2)
upper confidence bound
(2)
regret minimization
(2)
arm identification
(2)
preference data
(2)
active learning
(2)
instruction following
(2)
constrained optimization
(2)
regret bound
(2)
collaborative filtering
(1)
model misspecification
(1)
Papers
AdvancedIF: Rubric-Based Benchmarking and Reinforcement Learning for Advancing LLM Instruction Following
ACL 2026
AutoMixAlign: Adaptive Data Mixing for Multi-Task Preference Optimization in LLMs
ACL 2025
InfoPO: On Mutual Information Maximization for Large Language Model Alignment
NAACL 2025
Evolutionary Contrastive Distillation for Language Model Alignment
EMNLP 2024
HYPO: Hyperspherical Out-Of-Distribution Generalization
ICLR 2024
GALAXY: Graph-based Active Learning at the Extreme
ICML 2022
Near Instance Optimal Model Selection for Pure Exploration Linear Bandits
AISTATS 2022
Similarity Search for Efficient Active Learning and Search of Rare Concepts
AAAI 2022
Training OOD Detectors in their Natural Habitats
ICML 2022
Experimental Design for Regret Minimization in Linear Bandits
AISTATS 2021
High-dimensional Experimental Design and Kernel Bandits
ICML 2021
Improved Algorithms for Agnostic Pool-based Active Classification
ICML 2021
Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers
NeurIPS 2021
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits
NeurIPS 2020
The True Sample Complexity of Identifying Good Arms
AISTATS 2020
Decontamination of Mutual Contamination Models
JMLR 2019
Top Feasible Arm Identification
AISTATS 2019
Feasible Arm Identification
ICML 2018
Nonparametric Preference Completion
AISTATS 2018