Amir Yazdanbakhsh
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
38
Venues
14
Active years
2010–2025
Best venue rank
A*
Where they publish
Papers
38 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | 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 |
| 2025 | ICLR | 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 |
| 2025 | ICLR | SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs. | Mohammad Mozaffari, Amir Yazdanbakhsh, Zhao Zhang, Maryam Mehri Dehnavi |
| 2025 | ICML | 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 |
| 2025 | ICML | 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 |
| 2025 | ICML | SLiM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression. | Mohammad Mozaffari, Amir Yazdanbakhsh, Maryam Mehri Dehnavi |
| 2025 | ISCA | RAGO: Systematic Performance Optimization for Retrieval-Augmented Generation Serving. | Wenqi Jiang, Suvinay Subramanian, Cat Graves, Gustavo Alonso, Amir Yazdanbakhsh, Vidushi Dadu |
| 2025 | ISCA | LIA: A Single-GPU LLM Inference Acceleration with Cooperative AMX-Enabled CPU-GPU Computation and CXL Offloading. | Hyungyo Kim, Nachuan Wang, Qirong Xia, Jinghan Huang, Amir Yazdanbakhsh, Nam Sung Kim |
| 2025 | ISCA | Concorde: Fast and Accurate CPU Performance Modeling with Compositional Analytical-ML Fusion. | Arash Nasr-Esfahany, Mohammad Alizadeh, Victor Lee, Hanna Alam, Brett W. Coon, David E. Culler, Vidushi Dadu, Martin Dixon, Henry M. Levy, Santosh Pandey, Parthasarathy Ranganathan, Amir Yazdanbakhsh |
| 2024 | ASPLOS | Tandem Processor: Grappling with Emerging Operators in Neural Networks. | Soroush Ghodrati, Sean Kinzer, Hanyang Xu, Rohan Mahapatra, Yoonsung Kim, Byung Hoon Ahn, Dong Kai Wang, Lavanya Karthikeyan, Amir Yazdanbakhsh, Jongse Park, Nam Sung Kim, Hadi Esmaeilzadeh |
| 2024 | ASPLOS | In-Storage Domain-Specific Acceleration for Serverless Computing. | Rohan Mahapatra, Soroush Ghodrati, Byung Hoon Ahn, Sean Kinzer, Shu-Ting Wang, Hanyang Xu, Lavanya Karthikeyan, Hardik Sharma, Amir Yazdanbakhsh, Mohammad Alian, Hadi Esmaeilzadeh |
| 2024 | ICASSP | USM-Lite: Quantization and Sparsity Aware Fine-Tuning for Speech Recognition with Universal Speech Models. | Shaojin Ding, David Qiu, David Rim, Yanzhang He, Oleg Rybakov, Bo Li, Rohit Prabhavalkar, Weiran Wang, Tara N. Sainath, Zhonglin Han, Jian Li, Amir Yazdanbakhsh, Shivani Agrawal |
| 2024 | ICLR | Learning Performance-Improving Code Edits. | Alexander Shypula, Aman Madaan, Yimeng Zeng, Uri Alon, Jacob R. Gardner, Yiming Yang, Milad Hashemi, Graham Neubig, Parthasarathy Ranganathan, Osbert Bastani, Amir Yazdanbakhsh |
| 2024 | ICML | 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 |
| 2024 | ISCA | DACAPO: Accelerating Continuous Learning in Autonomous Systems for Video Analytics. | Yoonsung Kim, Changhun Oh, Jinwoo Hwang, Wonung Kim, Seongryong Oh, Yubin Lee, Hardik Sharma, Amir Yazdanbakhsh, Jongse Park |
| 2024 | SIGMETRICS | TAO: Re-Thinking DL-based Microarchitecture Simulation. | Santosh Pandey, Amir Yazdanbakhsh, Hang Liu |
| 2023 | ASPLOS | FLAT: An Optimized Dataflow for Mitigating Attention Bottlenecks. | Sheng-Chun Kao, Suvinay Subramanian, Gaurav Agrawal, Amir Yazdanbakhsh, Tushar Krishna |
| 2023 | DAC | Architecture 2.0: Challenges and Opportunities. | Vijay Janapa Reddi, Amir Yazdanbakhsh |
| 2023 | EMNLP | What Makes Chain-of-Thought Prompting Effective? A Counterfactual Study. | Aman Madaan, Katherine Hermann, Amir Yazdanbakhsh |
| 2023 | ICML | STEP: Learning N: M Structured Sparsity Masks from Scratch with Precondition. | Yucheng Lu, Shivani Agrawal, Suvinay Subramanian, Oleg Rybakov, Christopher De Sa, Amir Yazdanbakhsh |
| 2023 | ISCA | ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design. | Srivatsan Krishnan, Amir Yazdanbakhsh, Shvetank Prakash, Jason Jabbour, Ikechukwu Uchendu, Susobhan Ghosh, Behzad Boroujerdian, Daniel Richins, Devashree Tripathy, Aleksandra Faust, Vijay Janapa Reddi |
| 2023 | ISCA | MESA: Microarchitecture Extensions for Spatial Architecture Generation. | Dong Kai Wang, Jiaqi Lou, Naiyin Jin, Edwin Mascarenhas, Rohan Mahapatra, Sean Kinzer, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Nam Sung Kim |
| 2022 | ICLR | Data-Driven Offline Optimization for Architecting Hardware Accelerators. | Aviral Kumar, Amir Yazdanbakhsh, Milad Hashemi, Kevin Swersky, Sergey Levine |
| 2022 | ISCA | Accelerating attention through gradient-based learned runtime pruning. | Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Mingu Kang |
| 2022 | MICRO | Sparse Attention Acceleration with Synergistic In-Memory Pruning and On-Chip Recomputation. | Amir Yazdanbakhsh, Ashkan Moradifirouzabadi, Zheng Li, Mingu Kang |
| 2020 | ICLR | Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation. | Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh |
| 2019 | ISCA | AxMemo: hardware-compiler co-design for approximate code memoization. | Zhenhong Liu, Amir Yazdanbakhsh, Dong Kai Wang, Hadi Esmaeilzadeh, Nam Sung Kim |
| 2018 | FCCM | FlexiGAN: An End-to-End Solution for FPGA Acceleration of Generative Adversarial Networks. | Amir Yazdanbakhsh, Michael Brzozowski, Behnam Khaleghi, Soroush Ghodrati, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh |
| 2018 | ISCA | SnaPEA: Predictive Early Activation for Reducing Computation in Deep Convolutional Neural Networks. | Vahideh Akhlaghi, Amir Yazdanbakhsh, Kambiz Samadi, Rajesh K. Gupta, Hadi Esmaeilzadeh |
| 2018 | ISCA | GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks. | Amir Yazdanbakhsh, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh |
| 2016 | DATE | Grater: An approximation workflow for exploiting data-level parallelism in FPGA acceleration. | Atieh Lotfi, Abbas Rahimi, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Rajesh K. Gupta |
| 2016 | HPCA | TABLA: A unified template-based framework for accelerating statistical machine learning. | Divya Mahajan, Jongse Park, Emmanuel Amaro, Hardik Sharma, Amir Yazdanbakhsh, Joon Kyung Kim, Hadi Esmaeilzadeh |
| 2016 | ISCA | Towards Statistical Guarantees in Controlling Quality Tradeoffs for Approximate Acceleration. | Divya Mahajan, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Hadi Esmaeilzadeh |
| 2015 | DATE | Axilog: language support for approximate hardware design. | Amir Yazdanbakhsh, Divya Mahajan, Bradley Thwaites, Jongse Park, Anandhavel Nagendrakumar, Sindhuja Sethuraman, Kartik Ramkrishnan, Nishanthi Ravindran, Rudra Jariwala, Abbas Rahimi, Hadi Esmaeilzadeh, Kia Bazargan |
| 2015 | MICRO | Neural acceleration for GPU throughput processors. | Amir Yazdanbakhsh, Jongse Park, Hardik Sharma, Pejman Lotfi-Kamran, Hadi Esmaeilzadeh |
| 2014 | ISCA | General-purpose code acceleration with limited-precision analog computation. | Rene St. Amant, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Hadi Esmaeilzadeh, Arjang Hassibi, Luis Ceze, Doug Burger |
| 2011 | DSD | Dynamic Soft Error Hardening via Joint Body Biasing and Dynamic Voltage Scaling. | Farshad Firouzi, Amir Yazdanbakhsh, Hamed Dorosti, Sied Mehdi Fakhraie |
| 2010 | DDECS | Instruction reliability analysis for embedded processors. | Ali Azarpeyvand, Mostafa E. Salehi, Farshad Firouzi, Amir Yazdanbakhsh, Sied Mehdi Fakhraie |