Igor Fedorov

According to our database, Igor Fedorov authored at least 42 papers between 2011 and 2024.

Collaborative distances:

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

2024

DεS: Delayed ε-Shrinking for Faster Once-For-All Training.

Aditya Annavajjala, Alind Khare, Animesh Agrawal, Igor Fedorov, Hugo Latapie, Myungjin Lee, Alexey Tumanov

CoRR, 2024

SpinQuant: LLM quantization with learned rotations.

Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort

CoRR, 2024

Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale.

Wei Wen, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Hang Yin, Weiwei Chu, Kaveh Hassani, Mengying Sun, Jiang Liu, Xu Wang, Lin Jiang, Yuxin Chen, Buyun Zhang, Xi Liu, Dehua Cheng, Zhengxing Chen, Guang Zhao, Fangqiu Han, Jiyan Yang, Yuchen Hao, Liang Xiong, Wen-Yen Chen

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

SiGeo: Sub-One-Shot NAS via Geometry of Loss Landscape.

Hua Zheng, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Wen-Yen Chen, Wei Wen

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases.

Zechun Liu, Changsheng Zhao, Forrest N. Iandola, Chen Lai, Yuandong Tian, Igor Fedorov, Yunyang Xiong, Ernie Chang, Yangyang Shi, Raghuraman Krishnamoorthi, Liangzhen Lai, Vikas Chandra

Proceedings of the Forty-first International Conference on Machine Learning, 2024

DεpS: Delayed ε-Shrinking for Faster Once-for-All Training.

Aditya Annavajjala, Alind Khare, Animesh Agrawal, Igor Fedorov, Hugo Latapie, Myungjin Lee, Alexey Tumanov

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

SiGeo: Sub-One-Shot NAS via Information Theory and Geometry of Loss Landscape.

Hua Zheng, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Wen-Yen Chen, Wei Wen

CoRR, 2023

DistDNAS: Search Efficient Feature Interactions within 2 Hours.

Tunhou Zhang, Wei Wen, Igor Fedorov, Xi Liu, Buyun Zhang, Fangqiu Han, Wen-Yen Chen, Yiping Han, Feng Yan, Hai Li, Yiran Chen

CoRR, 2023

PerfSAGE: Generalized Inference Performance Predictor for Arbitrary Deep Learning Models on Edge Devices.

Yuji Chai, Devashree Tripathy, Chuteng Zhou, Dibakar Gope, Igor Fedorov, Ramon Matas Navarro, David Brooks, Gu-Yeon Wei, Paul N. Whatmough

CoRR, 2023

Efficient Edge Inference by Selective Query.

Anil Kag, Igor Fedorov, Aditya Gangrade, Paul N. Whatmough, Venkatesh Saligrama

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Beam Asymmetry, Divergence and Energy Spread Effects on the Radiation from Planar Undulators.

Konstantin V. Zhukovsky, Igor Fedorov

Symmetry, 2022

Restructurable Activation Networks.

Kartikeya Bhardwaj, James Ward, Caleb Tung, Dibakar Gope, Lingchuan Meng, Igor Fedorov, Alex Chalfin, Paul N. Whatmough, Danny Loh

CoRR, 2022

UDC: Unified DNAS for Compressible TinyML Models.

Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough

CoRR, 2022

Magnitude-Aware Probabilistic Speaker Embeddings.

Nikita Kuzmin, Igor Fedorov, Alexey Sholokhov

Proceedings of the Odyssey 2022: The Speaker and Language Recognition Workshop, 28 June, 2022

UDC: Unified DNAS for Compressible TinyML Models for Neural Processing Units.

Igor Fedorov, Ramon Matas Navarro, Hokchhay Tann, Chuteng Zhou, Matthew Mattina, Paul N. Whatmough

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

A Two-Layer 3-D Reconstruction Method and Calibration for Multicamera-Based Volumetric Positioning and Characterization.

Igor Fedorov, Benny Thörnberg, Hiba H. Alqaysi, Najeem Lawal, Mattias O'Nils

IEEE Trans. Instrum. Meas., 2021

Spontaneous and Stimulated Undulator Radiation in Symmetric and Asymmetric Multi-Periodic Magnetic Fields.

Konstantin V. Zhukovsky, Igor Fedorov

Symmetry, 2021

A Temporal Boosted YOLO-Based Model for Birds Detection around Wind Farms.

Hiba H. Alqaysi, Igor Fedorov, Faisal Z. Qureshi, Mattias O'Nils

J. Imaging, 2021

Compressing RNNs to Kilobyte Budget for IoT Devices Using Kronecker Products.

Urmish Thakker, Igor Fedorov, Chu Zhou, Dibakar Gope, Matthew Mattina, Ganesh Dasika, Jesse G. Beu

ACM J. Emerg. Technol. Comput. Syst., 2021

MicroNets: Neural Network Architectures for Deploying TinyML Applications on Commodity Microcontrollers.

Colby R. Banbury, Chuteng Zhou, Igor Fedorov, Ramon Matas Navarro, Urmish Thakker, Dibakar Gope, Vijay Janapa Reddi, Matthew Mattina, Paul N. Whatmough

Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

2020

TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids.

Igor Fedorov, Marko Stamenovic, Carl Jensen, Li-Chia Yang, Ari Mandell, Yiming Gan, Matthew Mattina, Paul N. Whatmough

Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Mango: A Python Library for Parallel Hyperparameter Tuning.

Sandeep Singh Sandha, Mohit Aggarwal, Igor Fedorov, Mani B. Srivastava

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

SSGD: Sparsity-Promoting Stochastic Gradient Descent Algorithm for Unbiased Dnn Pruning.

Ching Hua Lee, Igor Fedorov, Bhaskar D. Rao, Harinath Garudadri

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Compressing RNNs for IoT devices by 15-38x using Kronecker Products.

Urmish Thakker, Jesse G. Beu, Dibakar Gope, Chu Zhou, Igor Fedorov, Ganesh Dasika, Matthew Mattina

CoRR, 2019

Pushing the limits of RNN Compression.

Urmish Thakker, Igor Fedorov, Jesse G. Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina

Proceedings of the Fifth Workshop on Energy Efficient Machine Learning and Cognitive Computing, 2019

SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers.

Igor Fedorov, Ryan P. Adams, Matthew Mattina, Paul N. Whatmough

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Design Exploration of Multi-Camera Dome.

Hiba H. Alqaysi, Najeem Lawal, Igor Fedorov, Benny Thörnberg, Mattias O'Nils

Proceedings of the 13th International Conference on Distributed Smart Cameras, 2019

2018

Structured Learning with Scale Mixture Priors.

Igor Fedorov

PhD thesis, 2018

Rectified Gaussian Scale Mixtures and the Sparse Non-Negative Least Squares Problem.

Alican Nalci, Igor Fedorov, Maher Al-Shoukairi, Thomas T. Liu, Bhaskar D. Rao

IEEE Trans. Signal Process., 2018

A unified framework for sparse non-negative least squares using multiplicative updates and the non-negative matrix factorization problem.

Igor Fedorov, Alican Nalci, Ritwik Giri, Bhaskar D. Rao, Truong Q. Nguyen, Harinath Garudadri

Signal Process., 2018

Multimodal Sparse Bayesian Dictionary Learning.

Igor Fedorov, Bhaskar D. Rao

CoRR, 2018

Re-Weighted Learning for Sparsifying Deep Neural Networks.

Igor Fedorov, Bhaskar D. Rao

CoRR, 2018

Towards calibration of outdoor multi-camera visual monitoring system.

Igor Fedorov, Najeem Lawal, Benny Thörnberg, Hiba H. Alqaysi, Mattias O'Nils

Proceedings of the 12th International Conference on Distributed Smart Cameras, 2018

Full Coverage Optimization for Multi Camera Dome Placement in Volumetric Monitoring.

Hiba H. Alqaysi, Najeem Lawal, Igor Fedorov, Mattias O'Nils

Proceedings of the 12th International Conference on Distributed Smart Cameras, 2018

2017

Relevance Subject Machine: A Novel Person Re-identification Framework.

Igor Fedorov, Ritwik Giri, Bhaskar D. Rao, Truong Q. Nguyen

CoRR, 2017

Placement Strategy of Multi-Camera Volumetric Surveillance System for Activities Monitoring.

Igor Fedorov, Najeem Lawal, Mattias O'Nils, Hiba H. Alqaysi

Proceedings of the 11th International Conference on Distributed Smart Cameras, 2017

Evaluating Coverage Effectiveness of Multi-Camera Domes Placement for Volumetric Surveillance.

Hiba H. Alqaysi, Najeem Lawal, Igor Fedorov, Mattias O'Nils

Proceedings of the 11th International Conference on Distributed Smart Cameras, 2017

Multimodal sparse Bayesian dictionary learning applied to multimodal data classification.

Igor Fedorov, Bhaskar D. Rao, Truong Q. Nguyen

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Spect image reconstruction under imaging time constraints.

Igor Fedorov, Sebastian Obrzut, Bongyong Song, Bhaskar D. Rao

Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016

Rectified Gaussian Scale Mixtures and the Sparse Non-Negative Least Squares Problem.

Alican Nalci, Igor Fedorov, Bhaskar D. Rao

CoRR, 2016

Robust Bayesian method for simultaneous block sparse signal recovery with applications to face recognition.

Igor Fedorov, Ritwik Giri, Bhaskar D. Rao, Truong Q. Nguyen

Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

2011

Power delivery for series connected voltage domains in digital circuits.

Pradeep S. Shenoy, Igor Fedorov, Tyler Neyens, Philip T. Krein

Proceedings of the International Conference on Energy Aware Computing, 2011