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2020 – today
- 2024
[i30]Jordan Juravsky, Bradley C. A. Brown, Ryan Saul Ehrlich, Daniel Y. Fu, Christopher Ré, Azalia Mirhoseini:
Hydragen: High-Throughput LLM Inference with Shared Prefixes. CoRR abs/2402.05099 (2024)- [i29]Je-Yong Lee, Donghyun Lee, Genghan Zhang, Mo Tiwari, Azalia Mirhoseini:
CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models. CoRR abs/2404.08763 (2024) - [i28]Shayan Talaei, Mohammadreza Pourreza, Yu-Chen Chang, Azalia Mirhoseini, Amin Saberi:
CHESS: Contextual Harnessing for Efficient SQL Synthesis. CoRR abs/2405.16755 (2024) - [i27]Ali Momeni, Babak Rahmani, Benjamin Scellier, Logan G. Wright, Peter L. McMahon, Clara C. Wanjura, Yuhang Li, Anas Skalli, Natalia G. Berloff, Tatsuhiro Onodera, Ilker Oguz
, Francesco Morichetti, Philipp del Hougne, Manuel Le Gallo, Abu Sebastian, Azalia Mirhoseini, Cheng Zhang, Danijela Markovic, Daniel Brunner, Christophe Moser, Sylvain Gigan, Florian Marquardt, Aydogan Ozcan, Julie Grollier, Andrea J. Liu, Demetri Psaltis, Andrea Alù, Romain Fleury:
Training of Physical Neural Networks. CoRR abs/2406.03372 (2024) - [i26]Bradley C. A. Brown, Jordan Juravsky, Ryan Saul Ehrlich, Ronald Clark, Quoc V. Le, Christopher Ré, Azalia Mirhoseini:
Large Language Monkeys: Scaling Inference Compute with Repeated Sampling. CoRR abs/2407.21787 (2024) - [i25]Jon Saad-Falcon, Adrian Gamarra Lafuente, Shlok Natarajan, Nahum Maru, Hristo Todorov, Etash Guha, Estefany Kelly Buchanan, Mayee Chen, Neel Guha, Christopher Ré, Azalia Mirhoseini:
Archon: An Architecture Search Framework for Inference-Time Techniques. CoRR abs/2409.15254 (2024) - 2023
- [c39]Neel Guha, Mayee F. Chen, Kush Bhatia, Azalia Mirhoseini, Frederic Sala, Christopher Ré:
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification. NeurIPS 2023 - [i24]Deep Ganguli, Amanda Askell, Nicholas Schiefer, Thomas I. Liao, Kamile Lukosiute, Anna Chen, Anna Goldie, Azalia Mirhoseini, Catherine Olsson, Danny Hernandez, Dawn Drain, Dustin Li, Eli Tran-Johnson, Ethan Perez, Jackson Kernion, Jamie Kerr, Jared Mueller, Joshua Landau, Kamal Ndousse, Karina Nguyen, Liane Lovitt, Michael Sellitto, Nelson Elhage, Noemí Mercado, Nova DasSarma, Oliver Rausch, Robert Lasenby, Robin Larson, Sam Ringer, Sandipan Kundu, Saurav Kadavath, Scott Johnston, Shauna Kravec, Sheer El Showk, Tamera Lanham, Timothy Telleen-Lawton, Tom Henighan, Tristan Hume, Yuntao Bai, Zac Hatfield-Dodds, Ben Mann, Dario Amodei, Nicholas Joseph, Sam McCandlish, Tom Brown, Christopher Olah, Jack Clark, Samuel R. Bowman, Jared Kaplan:
The Capacity for Moral Self-Correction in Large Language Models. CoRR abs/2302.07459 (2023) - [i23]Neel Guha, Mayee F. Chen, Kush Bhatia, Azalia Mirhoseini, Frederic Sala, Christopher Ré:
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification. CoRR abs/2307.11031 (2023) - [i22]Sandipan Kundu, Yuntao Bai, Saurav Kadavath, Amanda Askell, Andrew Callahan, Anna Chen, Anna Goldie, Avital Balwit, Azalia Mirhoseini, Brayden McLean, Catherine Olsson, Cassie Evraets, Eli Tran-Johnson, Esin Durmus, Ethan Perez, Jackson Kernion, Jamie Kerr, Kamal Ndousse, Karina Nguyen, Nelson Elhage, Newton Cheng, Nicholas Schiefer, Nova DasSarma, Oliver Rausch, Robin Larson, Shannon Yang, Shauna Kravec, Timothy Telleen-Lawton, Thomas I. Liao, Tom Henighan, Tristan Hume, Zac Hatfield-Dodds, Sören Mindermann, Nicholas Joseph, Sam McCandlish, Jared Kaplan:
Specific versus General Principles for Constitutional AI. CoRR abs/2310.13798 (2023) - 2022
- [c38]Ahmet Faruk Budak, Zixuan Jiang, Keren Zhu, Azalia Mirhoseini, Anna Goldie, David Z. Pan:
Reinforcement Learning for Electronic Design Automation: Case Studies and Perspectives: (Invited Paper). ASP-DAC 2022: 500-505 - [c37]Dan Zhang, Safeen Huda, Ebrahim M. Songhori, Kartik Prabhu, Quoc V. Le, Anna Goldie, Azalia Mirhoseini:
A full-stack search technique for domain optimized deep learning accelerators. ASPLOS 2022: 27-42 - [c36]Paras Jain, Safeen Huda, Martin Maas, Joseph E. Gonzalez, Ion Stoica, Azalia Mirhoseini:
Learning to Design Accurate Deep Learning Accelerators with Inaccurate Multipliers. DATE 2022: 184-189 - [c35]Summer Yue, Ebrahim M. Songhori, Joe Wenjie Jiang, Toby Boyd, Anna Goldie, Azalia Mirhoseini, Sergio Guadarrama:
Scalability and Generalization of Circuit Training for Chip Floorplanning. ISPD 2022: 65-70 - [c34]Xinfeng Xie, Prakash Prabhu, Ulysse Beaugnon, Phitchaya Mangpo Phothilimthana, Sudip Roy, Azalia Mirhoseini, Eugene Brevdo, James Laudon, Yanqi Zhou:
A Transferable Approach for Partitioning Machine Learning Models on Multi-Chip-Modules. MLSys 2022 - [c33]Thien Duc Nguyen, Phillip Rieger, Huili Chen, Hossein Yalame, Helen Möllering, Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Shaza Zeitouni, Farinaz Koushanfar, Ahmad-Reza Sadeghi, Thomas Schneider:
FLAME: Taming Backdoors in Federated Learning. USENIX Security Symposium 2022: 1415-1432 - [i21]Zhanghao Wu, Paras Jain, Matthew A. Wright, Azalia Mirhoseini, Joseph E. Gonzalez, Ion Stoica:
Representing Long-Range Context for Graph Neural Networks with Global Attention. CoRR abs/2201.08821 (2022) - [i20]Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez, Edwin Chen, Craig Pettit, Scott Heiner, Kamile Lukosiute, Amanda Askell, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, Christopher Olah, Daniela Amodei, Dario Amodei, Dawn Drain, Dustin Li, Eli Tran-Johnson, Jackson Kernion, Jamie Kerr, Jared Mueller, Jeffrey Ladish, Joshua Landau, Kamal Ndousse, Liane Lovitt, Nelson Elhage, Nicholas Schiefer, Nicholas Joseph, Noemí Mercado, Nova DasSarma, Robin Larson, Sam McCandlish, Sandipan Kundu, Scott Johnston, Shauna Kravec, Sheer El Showk, Stanislav Fort, Timothy Telleen-Lawton, Tom Brown, Tom Henighan, Tristan Hume, Yuntao Bai, Zac Hatfield-Dodds, Ben Mann, Jared Kaplan:
Measuring Progress on Scalable Oversight for Large Language Models. CoRR abs/2211.03540 (2022) - [i19]Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, Carol Chen, Catherine Olsson, Christopher Olah, Danny Hernandez, Dawn Drain, Deep Ganguli, Dustin Li, Eli Tran-Johnson, Ethan Perez, Jamie Kerr, Jared Mueller, Jeffrey Ladish, Joshua Landau, Kamal Ndousse, Kamile Lukosiute, Liane Lovitt, Michael Sellitto, Nelson Elhage, Nicholas Schiefer, Noemí Mercado, Nova DasSarma, Robert Lasenby, Robin Larson, Sam Ringer, Scott Johnston, Shauna Kravec, Sheer El Showk, Stanislav Fort, Tamera Lanham, Timothy Telleen-Lawton, Tom Conerly, Tom Henighan, Tristan Hume, Samuel R. Bowman, Zac Hatfield-Dodds, Ben Mann, Dario Amodei, Nicholas Joseph, Sam McCandlish, Tom Brown, Jared Kaplan:
Constitutional AI: Harmlessness from AI Feedback. CoRR abs/2212.08073 (2022) - 2021
- [j8]Azalia Mirhoseini, Anna Goldie, Mustafa Yazgan, Joe Wenjie Jiang, Ebrahim M. Songhori, Shen Wang, Young-Joon Lee, Eric Johnson, Omkar Pathak, Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, Jeff Dean:
A graph placement methodology for fast chip design. Nat. 594(7862): 207-212 (2021) - [c32]Anna Goldie, Azalia Mirhoseini:
Reinforcement Learning for Placement Optimization. ISPD 2021: 5 - [c31]Zixuan Jiang, Ebrahim M. Songhori, Shen Wang, Anna Goldie, Azalia Mirhoseini, Joe W. J. Jiang, Young-Joon Lee, David Z. Pan:
Delving into Macro Placement with Reinforcement Learning. MLCAD 2021: 1-3 - [c30]Zhanghao Wu, Paras Jain, Matthew A. Wright, Azalia Mirhoseini, Joseph E. Gonzalez, Ion Stoica:
Representing Long-Range Context for Graph Neural Networks with Global Attention. NeurIPS 2021: 13266-13279 - [c29]Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Helen Möllering, Thien Duc Nguyen, Phillip Rieger, Ahmad-Reza Sadeghi, Thomas Schneider, Hossein Yalame, Shaza Zeitouni:
SAFELearn: Secure Aggregation for private FEderated Learning. SP (Workshops) 2021: 56-62 - [i18]Thien Duc Nguyen, Phillip Rieger, Hossein Yalame, Helen Möllering, Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Ahmad-Reza Sadeghi, Thomas Schneider, Shaza Zeitouni:
FLGUARD: Secure and Private Federated Learning. CoRR abs/2101.02281 (2021) - [i17]Dan Zhang, Safeen Huda, Ebrahim M. Songhori, Quoc V. Le, Anna Goldie, Azalia Mirhoseini:
A Full-stack Accelerator Search Technique for Vision Applications. CoRR abs/2105.12842 (2021) - [i16]Zixuan Jiang, Ebrahim M. Songhori, Shen Wang, Anna Goldie, Azalia Mirhoseini, Joe W. J. Jiang, Young-Joon Lee, David Z. Pan:
Delving into Macro Placement with Reinforcement Learning. CoRR abs/2109.02587 (2021) - [i15]Xinfeng Xie, Prakash Prabhu, Ulysse Beaugnon, Phitchaya Mangpo Phothilimthana, Sudip Roy, Azalia Mirhoseini, Eugene Brevdo, James Laudon, Yanqi Zhou:
A Transferable Approach for Partitioning Machine Learning Models on Multi-Chip-Modules. CoRR abs/2112.04041 (2021) - [i14]Thien Duc Nguyen, Phillip Rieger, Hossein Yalame, Helen Möllering, Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Ahmad-Reza Sadeghi, Thomas Schneider, Shaza Zeitouni:
FLGUARD: Secure and Private Federated Learning. IACR Cryptol. ePrint Arch. 2021: 25 (2021) - [i13]Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Helen Möllering, Thien Duc Nguyen, Phillip Rieger, Ahmad-Reza Sadeghi, Thomas Schneider, Hossein Yalame, Shaza Zeitouni:
SAFELearn: Secure Aggregation for private FEderated Learning. IACR Cryptol. ePrint Arch. 2021: 386 (2021) - 2020
- [j7]Yanqi Zhou, Sudip Roy, AmirAli Abdolrashidi, Daniel Lin-Kit Wong, Peter C. Ma, Qiumin Xu, Azalia Mirhoseini, James Laudon:
A Single-Shot Generalized Device Placement for Large Dataflow Graphs. IEEE Micro 40(5): 26-36 (2020) - [c28]Anna Goldie, Azalia Mirhoseini:
Placement Optimization with Deep Reinforcement Learning. ISPD 2020: 3-7 - [c27]Yanqi Zhou, Sudip Roy, AmirAli Abdolrashidi, Daniel Wong, Peter C. Ma, Qiumin Xu, Hanxiao Liu, Mangpo Phitchaya Phothilimtha, Shen Wang, Anna Goldie, Azalia Mirhoseini, James Laudon:
Transferable Graph Optimizers for ML Compilers. NeurIPS 2020 - [i12]Anna Goldie, Azalia Mirhoseini:
Placement Optimization with Deep Reinforcement Learning. CoRR abs/2003.08445 (2020) - [i11]Azalia Mirhoseini, Anna Goldie, Mustafa Yazgan, Joe W. J. Jiang, Ebrahim M. Songhori, Shen Wang, Young-Joon Lee, Eric Johnson, Omkar Pathak, Sungmin Bae, Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Anand Babu, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, Jeff Dean:
Chip Placement with Deep Reinforcement Learning. CoRR abs/2004.10746 (2020) - [i10]Yanqi Zhou, Sudip Roy, AmirAli Abdolrashidi, Daniel Wong, Peter C. Ma, Qiumin Xu, Hanxiao Liu, Mangpo Phitchaya Phothilimtha, Shen Wang, Anna Goldie, Azalia Mirhoseini, James Laudon:
Transferable Graph Optimizers for ML Compilers. CoRR abs/2010.12438 (2020)
2010 – 2019
- 2019
- [c26]Xin Wang, Fisher Yu, Lisa Dunlap, Yi-An Ma, Ruth Wang, Azalia Mirhoseini, Trevor Darrell, Joseph E. Gonzalez:
Deep Mixture of Experts via Shallow Embedding. UAI 2019: 552-562 - [i9]Azade Nazi, Will Hang, Anna Goldie, Sujith Ravi, Azalia Mirhoseini:
GAP: Generalizable Approximate Graph Partitioning Framework. CoRR abs/1903.00614 (2019) - [i8]Qingpeng Cai, Will Hang, Azalia Mirhoseini, George Tucker, Jingtao Wang, Wei Wei:
Reinforcement Learning Driven Heuristic Optimization. CoRR abs/1906.06639 (2019) - [i7]Yanqi Zhou, Sudip Roy, AmirAli Abdolrashidi, Daniel Lin-Kit Wong, Peter C. Ma, Qiumin Xu, Ming Zhong, Hanxiao Liu, Anna Goldie, Azalia Mirhoseini, James Laudon:
GDP: Generalized Device Placement for Dataflow Graphs. CoRR abs/1910.01578 (2019) - [i6]Azade Nazi, Will Hang, Anna Goldie, Sujith Ravi, Azalia Mirhoseini:
Generalized Clustering by Learning to Optimize Expected Normalized Cuts. CoRR abs/1910.07623 (2019) - 2018
- [j6]Azalia Mirhoseini, Eva L. Dyer, Ebrahim M. Songhori, Richard G. Baraniuk, Farinaz Koushanfar:
RankMap: A Framework for Distributed Learning From Dense Data Sets. IEEE Trans. Neural Networks Learn. Syst. 29(7): 2717-2730 (2018) - [c25]Azalia Mirhoseini, Anna Goldie, Hieu Pham, Benoit Steiner, Quoc V. Le, Jeff Dean:
A Hierarchical Model for Device Placement. ICLR (Poster) 2018 - [c24]Henri E. Bal, Arindam Pal, Azalia Mirhoseini, Thomas P. Parnell:
Introduction to ParLearning 2018. IPDPS Workshops 2018: 852-853 - [c23]Azalia Mirhoseini:
ParLearning 2018 Invited Talk 2. IPDPS Workshops 2018: 855 - [i5]Xin Wang, Fisher Yu, Ruth Wang, Yi-An Ma, Azalia Mirhoseini, Trevor Darrell, Joseph E. Gonzalez:
Deep Mixture of Experts via Shallow Embedding. CoRR abs/1806.01531 (2018) - 2017
- [j5]Bita Darvish Rouhani, Azalia Mirhoseini, Farinaz Koushanfar:
RISE: An Automated Framework for Real-Time Intelligent Video Surveillance on FPGA. ACM Trans. Embed. Comput. Syst. 16(5s): 158:1-158:18 (2017) - [c22]Bita Darvish Rouhani, Azalia Mirhoseini, Farinaz Koushanfar:
Deep3: Leveraging Three Levels of Parallelism for Efficient Deep Learning. DAC 2017: 61:1-61:6 - [c21]Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, Jeff Dean:
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. ICLR (Poster) 2017 - [c20]Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean:
Device Placement Optimization with Reinforcement Learning. ICML 2017: 2430-2439 - [c19]Azalia Mirhoseini, Bita Darvish Rouhani, Ebrahim M. Songhori, Farinaz Koushanfar:
ExtDict: Extensible Dictionaries for Data- and Platform-Aware Large-Scale Learning. IPDPS Workshops 2017: 379-388 - [c18]Bita Darvish Rouhani, Azalia Mirhoseini, Farinaz Koushanfar:
TinyDL: Just-in-time deep learning solution for constrained embedded systems. ISCAS 2017: 1-4 - [i4]Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, Jeff Dean:
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. CoRR abs/1701.06538 (2017) - [i3]Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean:
Device Placement Optimization with Reinforcement Learning. CoRR abs/1706.04972 (2017) - 2016
- [j4]Azalia Mirhoseini, Bita Darvish Rouhani, Ebrahim M. Songhori, Farinaz Koushanfar:
Chime: Checkpointing Long Computations on Interm ittently Energized IoT Devices. IEEE Trans. Multi Scale Comput. Syst. 2(4): 277-290 (2016) - [j3]Bita Darvish Rouhani, Azalia Mirhoseini, Ebrahim M. Songhori, Farinaz Koushanfar:
Automated Real-Time Analysis of Streaming Big and Dense Data on Reconfigurable Platforms. ACM Trans. Reconfigurable Technol. Syst. 10(1): 8:1-8:22 (2016) - [c17]Bita Darvish Rouhani, Azalia Mirhoseini, Farinaz Koushanfar:
Going deeper than deep learning for massive data analytics under physical constraints. CODES+ISSS 2016: 17:1-17:3 - [c16]Azalia Mirhoseini, Bita Darvish Rouhani, Ebrahim M. Songhori, Farinaz Koushanfar:
Perform-ML: performance optimized machine learning by platform and content aware customization. DAC 2016: 20:1-20:6 - [c15]Azalia Mirhoseini, Ahmad-Reza Sadeghi, Farinaz Koushanfar:
CryptoML: Secure outsourcing of big data machine learning applications. HOST 2016: 149-154 - [c14]Bita Darvish Rouhani, Azalia Mirhoseini, Farinaz Koushanfar:
DeLight: Adding Energy Dimension To Deep Neural Networks. ISLPED 2016: 112-117 - [c13]Raajen Patel, Tom Goldstein, Eva L. Dyer, Azalia Mirhoseini, Richard G. Baraniuk:
Deterministic Column Sampling for Low-Rank Matrix Approximation: Nyström vs. Incomplete Cholesky Decomposition. SDM 2016: 594-602 - 2015
- [j2]Azalia Mirhoseini, Miodrag Potkonjak, Farinaz Koushanfar:
Phase Change Memory Write Cost Minimization by Data Encoding. IEEE J. Emerg. Sel. Topics Circuits Syst. 5(1): 51-63 (2015) - [c12]Ebrahim M. Songhori, Azalia Mirhoseini, Xuyang Lu, Farinaz Koushanfar:
AHEAD: automated framework for hardware accelerated iterative data analysis. DATE 2015: 942-947 - [c11]Bita Darvish Rouhani, Ebrahim M. Songhori, Azalia Mirhoseini, Farinaz Koushanfar:
SSketch: An Automated Framework for Streaming Sketch-Based Analysis of Big Data on FPGA. FCCM 2015: 187-194 - [c10]Farinaz Koushanfar, Azalia Mirhoseini, Gang Qu, Zhiru Zhang:
DA Systemization of Knowledge: A Catalog of Prior Forward-Looking Initiatives. ICCAD 2015: 255-262 - [c9]Azalia Mirhoseini, Ebrahim M. Songhori, Bita Darvish Rouhani, Farinaz Koushanfar:
Flexible Transformations For Learning Big Data. SIGMETRICS 2015: 453-454 - [i2]Azalia Mirhoseini, Eva L. Dyer, Ebrahim M. Songhori, Richard G. Baraniuk, Farinaz Koushanfar:
RankMap: A Platform-Aware Framework for Distributed Learning from Dense Datasets. CoRR abs/1503.08169 (2015) - [i1]Raajen Patel, Thomas A. Goldstein, Eva L. Dyer, Azalia Mirhoseini, Richard G. Baraniuk:
oASIS: Adaptive Column Sampling for Kernel Matrix Approximation. CoRR abs/1505.05208 (2015) - 2013
- [c8]Azalia Mirhoseini, Ebrahim M. Songhori, Farinaz Koushanfar:
Automated checkpointing for enabling intensive applications on energy harvesting devices. ISLPED 2013: 27-32 - [c7]Azalia Mirhoseini, Ebrahim M. Songhori, Farinaz Koushanfar:
Idetic: A high-level synthesis approach for enabling long computations on transiently-powered ASICs. PerCom 2013: 216-224 - 2012
- [c6]Azalia Mirhoseini, Miodrag Potkonjak, Farinaz Koushanfar:
Coding-based energy minimization for phase change memory. DAC 2012: 68-76 - 2011
- [j1]Farinaz Koushanfar, Azalia Mirhoseini:
A Unified Framework for Multimodal Submodular Integrated Circuits Trojan Detection. IEEE Trans. Inf. Forensics Secur. 6(1): 162-174 (2011) - [c5]Azalia Mirhoseini, Farinaz Koushanfar:
HypoEnergy. Hybrid supercapacitor-battery power-supply optimization for Energy efficiency. DATE 2011: 887-890 - [c4]Farinaz Koushanfar, Azalia Mirhoseini:
Hybrid heterogeneous energy supply networks. ISCAS 2011: 2489-2492 - [c3]Azalia Mirhoseini, Farinaz Koushanfar:
Learning to manage combined energy supply systems. ISLPED 2011: 229-234 - 2010
- [c2]Azalia Mirhoseini, Yousra Alkabani, Farinaz Koushanfar:
Real time emulations: foundation and applications. DAC 2010: 623-624 - [c1]Farinaz Koushanfar, Azalia Mirhoseini, Yousra Alkabani:
A Unified Submodular Framework for Multimodal IC Trojan Detection. Information Hiding 2010: 17-32
Coauthor Index
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