Yazdanbakhsh, Amir

17 publications

ICLR 2025 Effective Interplay Between Sparsity and Quantization: From Theory to Practice Simla Burcu Harma, Ayan Chakraborty, Elizaveta Kostenok, Danila Mishin, Dongho Ha, Babak Falsafi, Martin Jaggi, Ming Liu, Yunho Oh, Suvinay Subramanian, Amir Yazdanbakhsh

ICML 2025 Learning to Keep a Promise: Scaling Language Model Decoding Parallelism with Learned Asynchronous Decoding Tian Jin, Ellie Y Cheng, Zachary Ankner, Nikunj Saunshi, Blake M Elias, Amir Yazdanbakhsh, Jonathan Ragan-Kelley, Suvinay Subramanian, Michael Carbin

CPAL 2025 Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna

ICML 2025 SLiM: One-Shot Quantization and Sparsity with Low-Rank Approximation for LLM Weight Compression Mohammad Mozaffari, Amir Yazdanbakhsh, Maryam Mehri Dehnavi

ICLR 2025 SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs Mohammad Mozaffari, Amir Yazdanbakhsh, Zhao Zhang, Maryam Mehri Dehnavi

ICML 2025 SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity Samir Khaki, Xiuyu Li, Junxian Guo, Ligeng Zhu, Konstantinos N. Plataniotis, Amir Yazdanbakhsh, Kurt Keutzer, Song Han, Zhijian Liu

ICLR 2025 The Journey Matters: Average Parameter Count over Pre-Training Unifies Sparse and Dense Scaling Laws Tian Jin, Ahmed Imtiaz Humayun, Utku Evci, Suvinay Subramanian, Amir Yazdanbakhsh, Dan Alistarh, Gintare Karolina Dziugaite

NeurIPS 2024 CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming Ali TehraniJamsaz, Arijit Bhattacharjee, Le Chen, Nesreen K. Ahmed, Amir Yazdanbakhsh, Ali Jannesari

CPAL 2024 Jaxpruner: A Concise Library for Sparsity Research Joo Hyung Lee, Wonpyo Park, Nicole Elyse Mitchell, Jonathan Pilault, Johan Samir Obando Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Woohyun Han, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J.C. Bik, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci

ICLR 2024 Learning Performance-Improving Code Edits Alexander G Shypula, Aman Madaan, Yimeng Zeng, Uri Alon, Jacob R. Gardner, Yiming Yang, Milad Hashemi, Graham Neubig, Parthasarathy Ranganathan, Osbert Bastani, Amir Yazdanbakhsh

NeurIPS 2024 ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization Haoran You, Yipin Guo, Yichao Fu, Wei Zhou, Huihong Shi, Xiaofan Zhang, Souvik Kundu, Amir Yazdanbakhsh, Yingyan Lin

ICML 2024 When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models Haoran You, Yichao Fu, Zheng Wang, Amir Yazdanbakhsh, Yingyan Celine Lin

ICML 2023 STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition Yucheng Lu, Shivani Agrawal, Suvinay Subramanian, Oleg Rybakov, Christopher De Sa, Amir Yazdanbakhsh

NeurIPS 2023 Self-Refine: Iterative Refinement with Self-Feedback Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark

ICLR 2022 Data-Driven Offline Optimization for Architecting Hardware Accelerators Aviral Kumar, Amir Yazdanbakhsh, Milad Hashemi, Kevin Swersky, Sergey Levine

ICLR 2020 Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh

ICLR 2020 Tpo: Tree Search Policy Optimization for Continuous Action Spaces Amir Yazdanbakhsh, Ebrahim Songhori, Robert Ormandi, Anna Goldie, Azalia Mirhoseini