Hisashi Kashima
36 papers · 2007–2026 · 15 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (13) π Conference Polyglot (15)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Academic Marathon
(19)
π
Keyword Trendsetter Combo
(4)
π
Keyword Champion
π₯
Unstoppable
(9)
π
Trend Setter
π
Century Club
(35)
ποΈ
Keyword Collector
(180)
β‘
Prolific Year
(6)
π
Conference Pioneer
Conferences
NIPS (10)
AAAI (4)
IJCAI (4)
ICML (3)
ACML (2)
AISTATS (2)
COLING (2)
WACV (2)
AACL (1)
COLT (1)
CVPR (1)
EACL (1)
EMNLP (1)
IJCNLP (1)
UAI (1)
Top co-authors
Research topics
Keywords
source-free domain adaptation
(3)
causal inference
(3)
optimal transport
(2)
counterfactual evaluation
(2)
domain shift
(2)
domain adaptation
(2)
attack detection
(2)
active learning
(2)
student modeling
(2)
graph neural network
(2)
knowledge tracing
(2)
prompt injection
(2)
transfer learning
(1)
reinforcement learning
(1)
ordinal regression
(1)
probabilistic modeling
(1)
learning theory
(1)
model selection
(1)
text classification
(1)
offline reinforcement learning
(1)
Papers
Unpacking the Implicit Norm Dynamics of Sharpness-Aware Minimization in Tensorized Models
AAAI 2026
Model-free Domain Adaptation for Concealed Multimodal Large-Language Models
WACV 2026
Counterfactual Evaluation for Blind Attack Detection in LLM-based Evaluation Systems
IJCNLP 2025
Counterfactual Evaluation for Blind Attack Detection in LLM-based Evaluation Systems
AACL 2025
Federated Source-Free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data
WACV 2025
Understanding and Improving Source-free Domain Adaptation from a Theoretical Perspective
CVPR 2024
Evaluating Saliency Explanations in NLP by Crowdsourcing
COLING 2024
AHP-Powered LLM Reasoning for Multi-Criteria Evaluation of Open-Ended Responses
EMNLP 2024
Enhancing Chess Reinforcement Learning with Graph Representation
NIPS 2024
Regularizing Neural Networks with Meta-Learning Generative Models
NIPS 2023
Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning
AAAI 2023
Feature selection for discovering distributional treatment effect modifiers
UAI 2022
Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations
AAAI 2022
Re-evaluating Word Moverβs Distance
ICML 2022
Regret Minimization for Causal Inference on Large Treatment Space
AISTATS 2021
Computationally Efficient Wasserstein Loss for Structured Labels
EACL 2021
Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint
AISTATS 2021
Performance as a Constraint: An Improved Wisdom of Crowds Using Performance Regularization
IJCAI 2020
Fast Unbalanced Optimal Transport on a Tree
NIPS 2020
Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance
ICML 2020
Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing
AAAI 2019
Active Change-Point Detection
ACML 2019
Fast Sparse Group Lasso
NIPS 2019
Approximation Ratios of Graph Neural Networks for Combinatorial Problems
NIPS 2019
Theoretical evidence for adversarial robustness through randomization
NIPS 2019
Learning to Sample Hard Instances for Graph Algorithms
ACML 2019
Simultaneous Clustering and Ranking from Pairwise Comparisons
IJCAI 2018
Progressive Comparison for Ranking Estimation
IJCAI 2016
Budgeted stream-based active learning via adaptive submodular maximization
NIPS 2016
Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem
COLT 2015
Latent Confusion Analysis by Normalized Gamma Construction
ICML 2014
Accurate Integration of Crowdsourced Labels Using Workersβ Self-Reported Confidence Scores
IJCAI 2013
Statistical Performance of Convex Tensor Decomposition
NIPS 2011
Training Conditional Random Fields Using Incomplete Annotations
COLING 2008
Multi-Task Learning via Conic Programming
NIPS 2007
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
NIPS 2007