Elias Jääsaari

13 papers A* 2A 1B 1Journal 8Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LEMUR: Learned Multi-Vector Retrieval. CoRR Elias Jääsaari, Ville Hyvönen, Teemu Roos
2025	J	`jnl`	VIBE: Vector Index Benchmark for Embeddings. CoRR Elias Jääsaari, Ville Hyvönen, Matteo Ceccarello, Teemu Roos, Martin Aumüller
2024	J	`jnl`	A Multilabel Classification Framework for Approximate Nearest Neighbor Search. J. Mach. Learn. Res. Ville Hyvönen, Elias Jääsaari, Teemu Roos
2024	A*	`conf`	LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search. NeurIPS Elias Jääsaari, Ville Hyvönen, Teemu Roos
2024	J	`jnl`	LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search. CoRR Elias Jääsaari, Ville Hyvönen, Teemu Roos
2024	J	`jnl`	Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures. CoRR Tomi Silander, Janne Leppä-aho, Elias Jääsaari, Teemu Roos
2022	A*	`conf`	A Multilabel Classification Framework for Approximate Nearest Neighbor Search. NeurIPS Ville Hyvönen, Elias Jääsaari, Teemu Roos
2022	J	`jnl`	SONAR: Joint Architecture and System Optimization Search. CoRR Elias Jääsaari, Michelle Ma, Ameet Talwalkar, Tianqi Chen
2019	—	`conf`	Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search. PAKDD (2) Elias Jääsaari, Ville Hyvönen, Teemu Roos
2019	J	`jnl`	Supervised Learning Approach to Approximate Nearest Neighbor Search. CoRR Ville Hyvönen, Elias Jääsaari, Teemu Roos
2018	J	`jnl`	Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search. CoRR Elias Jääsaari, Ville Hyvönen, Teemu Roos
2018	B	`conf`	Minimax Optimal Bayes Mixtures for Memoryless Sources over Large Alphabets. ALT Elias Jääsaari, Janne Leppä-aho, Tomi Silander, Teemu Roos
2018	A	`conf`	Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures. AISTATS Tomi Silander, Janne Leppä-aho, Elias Jääsaari, Teemu Roos