Taihei Oki
10 papers · 2022–2026 · 5 conferences · across top CS/AI conferences
Achievements
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๐บ๏ธ Taxonomy Completionist (18) ๐ Interdisciplinary Bridge ๐ฃ Hot Topic Early Bird ๐ Conference Polyglot (4) ๐งญ Keyword Pioneer
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Cross-Pollinator
(12)
๐๏ธ
Keyword Collector
(54)
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Century Club
(10)
Conferences
NIPS (6)
AAAI (1)
AISTATS (1)
COLT (1)
ICML (1)
Top co-authors
Keywords
combinatorial optimization
(4)
convex optimization
(4)
matroid intersection
(2)
bipartite matching
(2)
greedy algorithm
(2)
generalization bound
(2)
discrete optimization
(1)
multiclass classification
(1)
dimensionality reduction
(1)
low-rank approximation
(1)
mechanism design
(1)
map inference
(1)
online learning
(1)
linear programming
(1)
logistic loss
(1)
energy minimization
(1)
heuristic function
(1)
determinantal point process
(1)
multi-armed bandit
(1)
matrix approximation
(1)
Papers
Position Fair Mechanisms Allocating Indivisible Goods
AAAI 2026
No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting
NIPS 2024
Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming
NIPS 2024
Online Structured Prediction with FenchelโYoung Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss
COLT 2024
Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster $\text{L}$-/$\text{L}^\natural$-Convex Function Minimization
ICML 2023
Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation
AISTATS 2023
Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case
NIPS 2023
Lazy and Fast Greedy MAP Inference for Determinantal Point Process
NIPS 2022
Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search
NIPS 2022
Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions
NIPS 2022