Ali Abbasi

According to our database, Ali Abbasi authored at least 19 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

IO-SVD: Input-Output Whitened SVD for Adaptive-Rank LLM Compression.

Ali Abbasi, Chayne Thrash, Haoran Qin, Hamed Pirsiavash, Soheil Kolouri

CoRR, May, 2026

ConQuR: Corner Aligned Activation Quantization via Optimized Rotations for LLMs.

Chayne Thrash, Ali Abbasi, Soheil Kolouri

CoRR, May, 2026

Vector-Quantized Soft Label Compression for Dataset Distillation.

Ali Abbasi, Ashkan Shahbazi, Hamed Pirsiavash, Soheil Kolouri

CoRR, March, 2026

Zero Sum SVD: Balancing Loss Sensitivity for Low Rank LLM Compression.

Ali Abbasi, Chayne Thrash, Haoran Qin, Shansita D. Sharma, Sepehr Seifi, Soheil Kolouri

CoRR, February, 2026

2025

LUNA: Linear Universal Neural Attention with Generalization Guarantees.

Ashkan Shahbazi, Ping He, Ali Abbasi, Yikun Bai, Xinran Liu, Elaheh Akbari, Darian Salehi, Navid Naderializadeh, Soheil Kolouri

CoRR, December, 2025

Low-Rank Prehab: Preparing Neural Networks for SVD Compression.

Haoran Qin, Shansita D. Sharma, Ali Abbasi, Chayne Thrash, Soheil Kolouri

CoRR, December, 2025

MCNC: Manifold-Constrained Reparameterization for Neural Compression.

Chayne Thrash, Reed Andreas, Ali Abbasi, Parsa Nooralinejad, Soroush Abbasi Koohpayegani, Hamed Pirsiavash, Soheil Kolouri

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Diffusion-Augmented Coreset Expansion for Scalable Dataset Distillation.

Ali Abbasi, Shima Imani, Chenyang An, Gayathri Mahalingam, Harsh Shrivastava, Maurice Diesendruck, Hamed Pirsiavash, Pramod Sharma, Soheil Kolouri

CoRR, 2024

Next-Token Prediction Task Assumes Optimal Data Ordering for LLM Training in Proof Generation.

Chenyang An, Shima Imani, Feng Yao, Chengyu Dong, Ali Abbasi, Harsh Shrivastava, Samuel Buss, Jingbo Shang, Gayathri Mahalingam, Pramod Sharma, Maurice Diesendruck

CoRR, 2024

MCNC: Manifold Constrained Network Compression.

Chayne Thrash, Ali Abbasi, Parsa Nooralinejad, Soroush Abbasi Koohpayegani, Reed Andreas, Hamed Pirsiavash, Soheil Kolouri

CoRR, 2024

One Category One Prompt: Dataset Distillation using Diffusion Models.

Ali Abbasi, Ashkan Shahbazi, Hamed Pirsiavash, Soheil Kolouri

CoRR, 2024

Teaching Networks to Solve Optimization Problems.

Xinran Liu, Yuzhe Lu, Ali Abbasi, Meiyi Li, Javad Mohammadi, Soheil Kolouri

IEEE Access, 2024

Dynamic Online Modulation Recognition using Incremental Learning.

Ali Owfi, Ali Abbasi, Fatemeh Afghah, Jonathan D. Ashdown, Kurt A. Turck

Proceedings of the International Conference on Computing, Networking and Communications, 2024

BrainWash: A Poisoning Attack to Forget in Continual Learning.

Ali Abbasi, Parsa Nooralinejad, Hamed Pirsiavash, Soheil Kolouri

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Multi-Agent Lifelong Implicit Neural Learning.

Soheil Kolouri, Ali Abbasi, Soroush Abbasi Koohpayegani, Parsa Nooralinejad, Hamed Pirsiavash

IEEE Signal Process. Lett., 2023

CovarNav: Machine Unlearning via Model Inversion and Covariance Navigation.

Ali Abbasi, Chayne Thrash, Elaheh Akbari, Daniel Zhang, Soheil Kolouri

CoRR, 2023

PRANC: Pseudo RAndom Networks for Compacting deep models.

Parsa Nooralinejad, Ali Abbasi, Soroush Abbasi Koohpayegani, Kossar Pourahmadi Meibodi, Rana Muhammad Shahroz Khan, Soheil Kolouri, Hamed Pirsiavash

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

PRANC: Pseudo RAndom Networks for Compacting deep models.

Parsa Nooralinejad, Ali Abbasi, Soheil Kolouri, Hamed Pirsiavash

CoRR, 2022

Sparsity and Heterogeneous Dropout for Continual Learning in the Null Space of Neural Activations.

Ali Abbasi, Parsa Nooralinejad, Vladimir Braverman, Hamed Pirsiavash, Soheil Kolouri

Proceedings of the Conference on Lifelong Learning Agents, 2022