Martin Foltin

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 18

Top Topics

Electron Microscopy

Neural Network Training

Machine Learning

Top Venues

IEEE Internet Comput.

Publications

Ann Mary Justine Koomthanam, Aalap Tripathy, Sergey Serebryakov, Gyanaranjan Nayak, Martin Foltin, Suparna Bhattacharya
Common Metadata Framework: Integrated Framework for Trustworthy Artificial Intelligence Pipelines. IEEE Internet Comput. 28 (3) (2024)
Ashish Mishra, Gyanaranjan Nayak, Suparna Bhattacharya, Tarun Kumar, Arpit Shah, Martin Foltin
LLM-Guided Counterfactual Data Generation for Fairer AI. WWW (Companion Volume) (2024)
Gayathri Saranathan, Martin Foltin, Aalap Tripathy, Maxim A. Ziatdinov, Ann Mary Justine Koomthanam, Suparna Bhattacharya, Ayana Ghosh, Kevin Roccapriore, Sreenivas Rangan Sukumar, Paolo Faraboschi
Towards Rapid Autonomous Electron Microscopy with Active Meta-Learning. SC Workshops (2023)
Rafael Ferreira da Silva, Rosa M. Badia, Venkat Bala, Debbie Bard, Peer-Timo Bremer, Ian Buckley, Silvina Caíno-Lores, Kyle Chard, Carole A. Goble, Shantenu Jha, Daniel S. Katz, Daniel Laney, Manish Parashar, Frédéric Suter, Nick Tyler, Thomas D. Uram, Ilkay Altintas, Stefan Andersson, William Arndt, Juan Aznar, Jonathan Bader, Bartosz Balis, Chris Blanton, Kelly Rosa Braghetto, Aharon Brodutch, Paul Brunk, Henri Casanova, Alba Cervera-Lierta, Justin Chigu, Tainã Coleman, Nick Collier, Iacopo Colonnelli, Frederik Coppens, Michael R. Crusoe, Will Cunningham, Bruno de Paula Kinoshita, Paolo Di Tommaso, Charles M. Doutriaux, Matthew Downton, Wael R. Elwasif, Bjoern Enders, Chris Erdmann, Thomas Fahringer, Ludmilla Figueiredo, Rosa Filgueira, Martin Foltin, Anne Fouilloux, Luiz Gadelha, Andy Gallo, Artur García-Sáez, et al.
Workflows Community Summit 2022: A Roadmap Revolution. CoRR (2023)
Revathy Venkataramanan, Aalap Tripathy, Martin Foltin, Hong Yung Yip, Annmary Justine, Amit P. Sheth
Knowledge Graph Empowered Machine Learning Pipelines for Improved Efficiency, Reusability, and Explainability. IEEE Internet Comput. 27 (1) (2023)
Giacomo Pedretti, John Moon, Pedro Bruel, Sergey Serebryakov, Ron M. Roth, Luca Buonanno, Tobias Ziegler, Cong Xu, Martin Foltin, Paolo Faraboschi, Jim Ignowski, Catherine E. Graves
X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs. CoRR (2023)
Yeonju Ro, Cong Xu, Agnieszka Ciborowska, Suparna Bhattacharya, Frankie Li, Martin Foltin
Dataset Efficient Training with Model Ensembling. CVPR Workshops (2023)
Annmary Justine, Sergey Serebryakov, Cong Xu, Aalap Tripathy, Suparna Bhattacharya, Paolo Faraboschi, Martin Foltin
Self-learning Data Foundation for Scientific AI. SMC (2022)
Cong Xu, Suparna Bhattacharya, Martin Foltin, Suren Byna, Paolo Faraboschi
Data-Aware Storage Tiering for Deep Learning. PDSW@SC (2021)
Giacomo Pedretti, Catherine E. Graves, Can Li, Sergey Serebryakov, Xia Sheng, Martin Foltin, Ruibin Mao, John Paul Strachan
Tree-based machine learning performed in-memory with memristive analog CAM. CoRR (2021)
Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Sapan Agarwal, Matthew J. Marinella, Martin Foltin, John Paul Strachan, Dejan S. Milojicic, Wen-Mei Hwu, Kaushik Roy
PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-Efficient ReRAM. IEEE Trans. Computers 69 (8) (2020)
Martin Foltin, Glaucimar Aguiar, Rodrigo Antunes, Plínio Silveira, Gustavo Knuppe, Joao Ambrosi, Soumitra Chatterjee, Jitendra Onkar Kolhe, Sunil Lakshiminarashimha, Dejan S. Milojicic, John Paul Strachan, Craig Warner, Amit Sharma, Eddie Lee, Sai Rahul Chalamalasetti, Chris Brueggen, Charles Williams, Nathaniel Jansen, Felipe Saenz, Luis Federico Li
FPGA Demonstrator of a Programmable Ultra-Efficient Memristor-Based Machine Learning Inference Accelerator. ICRC (2019)
Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Sapan Agarwal, Matthew J. Marinella, Martin Foltin, John Paul Strachan, Dejan S. Milojicic, Wen-Mei W. Hwu, Kaushik Roy
PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-efficient ReRAM. CoRR (2019)
Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Geoffrey Ndu, Martin Foltin, R. Stanley Williams, Paolo Faraboschi, Wen-mei W. Hwu, John Paul Strachan, Kaushik Roy, Dejan S. Milojicic
PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference. ASPLOS (2019)
Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti, Geoffrey Ndu, Martin Foltin, R. Stanley Williams, Paolo Faraboschi, Wen-Mei Hwu, John Paul Strachan, Kaushik Roy, Dejan S. Milojicic
PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference. CoRR (2019)
Joao Ambrosi, Aayush Ankit, Rodrigo Antunes, Sai Rahul Chalamalasetti, Soumitra Chatterjee, Izzat El Hajj, Guilherme Fachini, Paolo Faraboschi, Martin Foltin, Sitao Huang, Wen-Mei Hwu, Gustavo Knuppe, Sunil Vishwanathpur Lakshminarasimha, Dejan S. Milojicic, Mohan Parthasarathy, Filipe Ribeiro, Lucas Rosa, Kaushik Roy, Plínio Silveira, John Paul Strachan
Hardware-Software Co-Design for an Analog-Digital Accelerator for Machine Learning. ICRC (2018)
Catherine E. Graves, Wen Ma, Xia Sheng, Brent Buchanan, Le Zheng, Sity Lam, Xuema Li, Sai Rahul Chalamalasetti, Lennie Kiyama, Martin Foltin, John Paul Strachan, Matthew P. Hardy
Regular Expression Matching with Memristor TCAMs for Network Security. NANOARCH (2018)
Catherine E. Graves, Wen Ma, Xia Sheng, Brent Buchanan, Le Zheng, Sity Lam, Xuema Li, Sai Rahul Chalamalasetti, Lennie Kiyama, Martin Foltin, Matthew P. Hardy, John Paul Strachan
Regular Expression Matching with Memristor TCAMs. ICRC (2018)
Martin Foltin, Brian Foutz, Sean Tyler
Efficient stimulus independent timing abstraction model based on a new concept of circuit block transparency. DAC (2002)
Ivan Sekaj, Martin Foltin, Michal Gonos
Genetic Algorithm Based Adaptive Control Of An Electromechanical MIMO System. GECCO (2002)