Jordan Dotzel - RankMe

21 papers A* 4A 1Journal 13Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Semantic Compression of 3D Objects for Open and Collaborative Virtual Worlds. CoRR Jordan Dotzel, Tony Montes, Mohamed S. Abdelfattah, Zhiru Zhang
2025	J	`jnl`	SparAMX: Accelerating Compressed LLMs Token Generation on AMX-powered CPUs. CoRR Ahmed F. AbouElhamayed, Jordan Dotzel, Yash Akhauri, Chi-Chih Chang, Sameh Gobriel, J. Pablo Muñoz, Vui Seng Chua, Nilesh Jain, Mohamed S. Abdelfattah
2024	—	`conf`	Exploring the Limits of Semantic Image Compression at Micro-bits per Pixel. Tiny Papers @ ICLR Jordan Dotzel, Bahaa Kotb, James Dotzel, Mohamed S. Abdelfattah, Zhiru Zhang
2024	J	`jnl`	Exploring the Limits of Semantic Image Compression at Micro-bits per Pixel. CoRR Jordan Dotzel, Bahaa Kotb, James Dotzel, Mohamed S. Abdelfattah, Zhiru Zhang
2024	—	`conf`	FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search. AutoML Jordan Dotzel, Gang Wu, Andrew Li, Muhammad Umar, Yun Ni, Mohamed S. Abdelfattah, Zhiru Zhang, Liqun Cheng, Martin G. Dixon, Norman P. Jouppi, Quoc V. Le, Sheng Li
2024	A*	`conf`	Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs. ICML Jordan Dotzel, Yuzong Chen, Bahaa Kotb, Sushma Prasad, Gang Wu, Sheng Li, Mohamed S. Abdelfattah, Zhiru Zhang
2024	J	`jnl`	Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs. CoRR Jordan Dotzel, Yuzong Chen, Bahaa Kotb, Sushma Prasad, Gang Wu, Sheng Li, Mohamed S. Abdelfattah, Zhiru Zhang
2024	J	`jnl`	Radial Networks: Dynamic Layer Routing for High-Performance Large Language Models. CoRR Jordan Dotzel, Yash Akhauri, Ahmed S. AbouElhamayed, Carly Jiang, Mohamed S. Abdelfattah, Zhiru Zhang
2024	A*	`conf`	ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models. EMNLP Yash Akhauri, Ahmed F. AbouElhamayed, Jordan Dotzel, Zhiru Zhang, Alexander M. Rush, Safeen Huda, Mohamed S. Abdelfattah
2024	J	`jnl`	ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models. CoRR Yash Akhauri, Ahmed F. AbouElhamayed, Jordan Dotzel, Zhiru Zhang, Alexander M. Rush, Safeen Huda, Mohamed S. Abdelfattah
2023	J	`jnl`	FLIQS: One-Shot Mixed-Precision Floating-Point and Integer Quantization Search. CoRR Jordan Dotzel, Gang Wu, Andrew Li, Muhammad Umar, Yun Ni, Mohamed S. Abdelfattah, Zhiru Zhang, Liqun Cheng, Martin G. Dixon, Norman P. Jouppi, Quoc V. Le, Sheng Li
2023	—	`conf`	M4BRAM: Mixed-Precision Matrix-Matrix Multiplication in FPGA Block RAMs. ICFPT Yuzong Chen, Jordan Dotzel, Mohamed S. Abdelfattah
2023	J	`jnl`	M4BRAM: Mixed-Precision Matrix-Matrix Multiplication in FPGA Block RAMs. CoRR Yuzong Chen, Jordan Dotzel, Mohamed S. Abdelfattah
2021	J	`jnl`	Enabling Design Methodologies and Future Trends for Edge AI: Specialization and Co-design. CoRR Cong Hao, Jordan Dotzel, Jinjun Xiong, Luca Benini, Zhiru Zhang, Deming Chen
2021	J	`jnl`	Enabling Design Methodologies and Future Trends for Edge AI: Specialization and Codesign. IEEE Des. Test Cong Hao, Jordan Dotzel, Jinjun Xiong, Luca Benini, Zhiru Zhang, Deming Chen
2021	A	`conf`	Logic Synthesis Meets Machine Learning: Trading Exactness for Generalization. DATE Shubham Rai, Walter Lau Neto, Yukio Miyasaka, Xinpei Zhang, Mingfei Yu, Qingyang Yi, Masahiro Fujita, Guilherme B. Manske, Matheus F. Pontes, Leomar S. da Rosa, Marilton S. de Aguiar, Paulo F. Butzen, Po-Chun Chien, Yu-Shan Huang, Hoa-Ren Wang, Jie-Hong R. Jiang, Jiaqi Gu, Zheng Zhao, Zixuan Jiang, David Z. Pan, Brunno A. Abreu, Isac de Souza Campos, Augusto Andre Souza Berndt, Cristina Meinhardt, Jônata Tyska Carvalho, Mateus Grellert, Sergio Bampi, Aditya Lohana, Akash Kumar, Wei Zeng, Azadeh Davoodi, Rasit Onur Topaloglu, Yuan Zhou, Jordan Dotzel, Yichi Zhang, Hanyu Wang, Zhiru Zhang, Valerio Tenace, Pierre-Emmanuel Gaillardon, Alan Mishchenko, Satrajit Chatterjee
2020	J	`jnl`	Logic Synthesis Meets Machine Learning: Trading Exactness for Generalization. CoRR Shubham Rai, Walter Lau Neto, Yukio Miyasaka, Xinpei Zhang, Mingfei Yu, Qingyang Yi, Masahiro Fujita, Guilherme B. Manske, Matheus F. Pontes, Leomar S. da Rosa Jr., Marilton S. de Aguiar, Paulo F. Butzen, Po-Chun Chien, Yu-Shan Huang, Hoa-Ren Wang, Jie-Hong R. Jiang, Jiaqi Gu, Zheng Zhao, Zixuan Jiang, David Z. Pan, Brunno A. Abreu, Isac de Souza Campos, Augusto Andre Souza Berndt, Cristina Meinhardt, Jônata Tyska Carvalho, Mateus Grellert, Sergio Bampi, Aditya Lohana, Akash Kumar, Wei Zeng, Azadeh Davoodi, Rasit Onur Topaloglu, Yuan Zhou, Jordan Dotzel, Yichi Zhang, Hanyu Wang, Zhiru Zhang, Valerio Tenace, Pierre-Emmanuel Gaillardon, Alan Mishchenko, Satrajit Chatterjee
2019	A*	`conf`	Building Efficient Deep Neural Networks With Unitary Group Convolutions. CVPR Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang
2019	A*	`conf`	Improving Neural Network Quantization without Retraining using Outlier Channel Splitting. ICML Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang
2019	J	`jnl`	Improving Neural Network Quantization without Retraining using Outlier Channel Splitting. CoRR Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang
2018	J	`jnl`	Building Efficient Deep Neural Networks with Unitary Group Convolutions. CoRR Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang