Nurbek Tastan - RankMe

20 papers A* 4A 1Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	MoSE: Mixture of Slimmable Experts for Efficient and Adaptive Language Models. CoRR Nurbek Tastan, Stefanos Laskaridis, Karthik Nandakumar, Samuel Horvath
2025	J	`jnl`	A Framework for Double-Blind Federated Adaptation of Foundation Models. CoRR Nurbek Tastan, Karthik Nandakumar
2025	A*	`conf`	Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks. ICML Nurbek Tastan, Samuel Horváth, Karthik Nandakumar
2025	J	`jnl`	Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks. CoRR Nurbek Tastan, Samuel Horváth, Karthik Nandakumar
2025	J	`jnl`	CYCle: Choosing Your Collaborators Wisely to Enhance Collaborative Fairness in Decentralized Learning. CoRR Nurbek Tastan, Samuel Horváth, Karthik Nandakumar
2025	J	`jnl`	CYCle: Choosing Your Collaborators Wisely to Enhance Collaborative Fairness in Decentralized Learning. Trans. Mach. Learn. Res. Nurbek Tastan, Samuel Horváth, Karthik Nandakumar
2025	—	`conf`	FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning. CPAL Nurbek Tastan, Samuel Horváth, Martin Takác, Karthik Nandakumar
2025	J	`jnl`	LoFT: Low-Rank Adaptation That Behaves Like Full Fine-Tuning. CoRR Nurbek Tastan, Stefanos Laskaridis, Martin Takác, Karthik Nandakumar, Samuel Horváth
2025	J	`jnl`	MOLM: Mixture of LoRA Markers. CoRR Samar Fares, Nurbek Tastan, Noor Hussein, Karthik Nandakumar
2025	J	`jnl`	SPDMark: Selective Parameter Displacement for Robust Video Watermarking. CoRR Samar Fares, Nurbek Tastan, Karthik Nandakumar
2025	J	`jnl`	Stochastic Self-Organization in Multi-Agent Systems. CoRR Nurbek Tastan, Samuel Horvath, Karthik Nandakumar
2024	A	`conf`	A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection. WACV Anas Al-lahham, Nurbek Tastan, Muhammad Zaigham Zaheer, Karthik Nandakumar
2024	A*	`conf`	Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New Baseline. CVPR Anas Al-lahham, Muhammad Zaigham Zaheer, Nurbek Tastan, Karthik Nandakumar
2024	J	`jnl`	Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New Baseline. CoRR Anas Al-lahham, Muhammad Zaigham Zaheer, Nurbek Tastan, Karthik Nandakumar
2024	J	`jnl`	FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning. CoRR Nurbek Tastan, Samuel Horváth, Martin Takác, Karthik Nandakumar
2024	A*	`conf`	Redefining Contributions: Shapley-Driven Federated Learning. IJCAI Nurbek Tastan, Samar Fares, Toluwani Aremu, Samuel Horváth, Karthik Nandakumar
2024	J	`jnl`	Redefining Contributions: Shapley-Driven Federated Learning. CoRR Nurbek Tastan, Samar Fares, Toluwani Aremu, Samuel Horváth, Karthik Nandakumar
2023	J	`jnl`	A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection. CoRR Anas Al-lahham, Nurbek Tastan, Muhammad Zaigham Zaheer, Karthik Nandakumar
2023	A*	`conf`	CaPriDe Learning: Confidential and Private Decentralized Learning Based on Encryption-Friendly Distillation Loss. CVPR Nurbek Tastan, Karthik Nandakumar
2019	—	`conf`	Burglary Detection Framework for House Crime Control. ICCSA (7) Nurbek Tastan, Abdul Razaque, Mohamed Ben Haj Frej, Amanzholova Saule Toksanovna, Raouf M. Ganda, Fathi H. Amsaad