Tahseen Rabbani

According to our database1, Tahseen Rabbani authored at least 18 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2025
Access Paths for Efficient Ordering with Large Language Models.
CoRR, September, 2025

Mitigating Unintended Memorization with LoRA in Federated Learning for LLMs.
CoRR, February, 2025

2024
Efficient Models and Learning Strategies for Resource-Constrained Systems.
PhD thesis, 2024

HashEvict: A Pre-Attention KV Cache Eviction Strategy using Locality-Sensitive Hashing.
CoRR, 2024

Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity.
CoRR, 2024

Calibrated Dataset Condensation for Faster Hyperparameter Search.
CoRR, 2024

Benchmarking the Robustness of Image Watermarks.
CoRR, 2024

conv_einsum: A Framework for Representation and Fast Evaluation of Multilinear Operations in Convolutional Tensorial Neural Networks.
CoRR, 2024

Balancing Label Imbalance in Federated Environments Using Only Mixup and Artificially-Labeled Noise.
Proceedings of the Pattern Recognition and Artificial Intelligence, 2024

A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM).
Proceedings of the Forty-first International Conference on Machine Learning, 2024

WAVES: Benchmarking the Robustness of Image Watermarks.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Large-Scale Distributed Learning via Private On-Device Locality-Sensitive Hashing.
CoRR, 2023

Large-Scale Distributed Learning via Private On-Device LSH.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Comfetch: Federated Learning of Large Networks on Memory-Constrained Clients via Sketching.
CoRR, 2021

Practical and Fast Momentum-Based Power Methods.
Proceedings of the Mathematical and Scientific Machine Learning, 2021

2020
Fast GPU Convolution for CP-Decomposed Tensorial Neural Networks.
Proceedings of the Intelligent Systems and Applications, 2020


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