Zobrazeno 1 - 10
of 627
pro vyhledávání: '"Stewart, Matthew A."'
Intelligent autonomous agents hold much potential for the domain of cyber-security. However, due to many state-of-the-art approaches relying on uninterpretable black-box models, there is growing demand for methods that offer stakeholders clear and ac
Externí odkaz:
http://arxiv.org/abs/2412.04367
Autor:
Banbury, Colby, Njor, Emil, Garavagno, Andrea Mattia, Stewart, Matthew, Warden, Pete, Kudlur, Manjunath, Jeffries, Nat, Fafoutis, Xenofon, Reddi, Vijay Janapa
Tiny machine learning (TinyML) for low-power devices lacks robust datasets for development. We present Wake Vision, a large-scale dataset for person detection that contains over 6 million quality-filtered images. We provide two variants: Wake Vision
Externí odkaz:
http://arxiv.org/abs/2405.00892
Autor:
Stewart, Matthew, Moss, Emanuel, Warden, Pete, Plancher, Brian, Kennedy, Susan, Sloane, Mona, Reddi, Vijay Janapa
Artificial intelligence systems connected to sensor-laden devices are becoming pervasive, which has significant implications for a range of AI risks, including to privacy, the environment, autonomy, and more. There is therefore a growing need for inc
Externí odkaz:
http://arxiv.org/abs/2402.11183
Autor:
Mayoral-Vilches, Víctor, Jabbour, Jason, Hsiao, Yu-Shun, Wan, Zishen, Crespo-Álvarez, Martiño, Stewart, Matthew, Reina-Muñoz, Juan Manuel, Nagras, Prateek, Vikhe, Gaurav, Bakhshalipour, Mohammad, Pinzger, Martin, Rass, Stefan, Panigrahi, Smruti, Corradi, Giulio, Roy, Niladri, Gibbons, Phillip B., Neuman, Sabrina M., Plancher, Brian, Reddi, Vijay Janapa
We introduce RobotPerf, a vendor-agnostic benchmarking suite designed to evaluate robotics computing performance across a diverse range of hardware platforms using ROS 2 as its common baseline. The suite encompasses ROS 2 packages covering the full r
Externí odkaz:
http://arxiv.org/abs/2309.09212
Autor:
Stewart, Matthew, Warden, Pete, Omri, Yasmine, Prakash, Shvetank, Santos, Joao, Hymel, Shawn, Brown, Benjamin, MacArthur, Jim, Jeffries, Nat, Katti, Sachin, Plancher, Brian, Reddi, Vijay Janapa
Machine learning (ML) sensors are enabling intelligence at the edge by empowering end-users with greater control over their data. ML sensors offer a new paradigm for sensing that moves the processing and analysis to the device itself rather than rely
Externí odkaz:
http://arxiv.org/abs/2306.08848
Autor:
Yik, Jason, Berghe, Korneel Van den, Blanken, Douwe den, Bouhadjar, Younes, Fabre, Maxime, Hueber, Paul, Ke, Weijie, Khoei, Mina A, Kleyko, Denis, Pacik-Nelson, Noah, Pierro, Alessandro, Stratmann, Philipp, Sun, Pao-Sheng Vincent, Tang, Guangzhi, Wang, Shenqi, Zhou, Biyan, Ahmed, Soikat Hasan, Joseph, George Vathakkattil, Leto, Benedetto, Micheli, Aurora, Mishra, Anurag Kumar, Lenz, Gregor, Sun, Tao, Ahmed, Zergham, Akl, Mahmoud, Anderson, Brian, Andreou, Andreas G., Bartolozzi, Chiara, Basu, Arindam, Bogdan, Petrut, Bohte, Sander, Buckley, Sonia, Cauwenberghs, Gert, Chicca, Elisabetta, Corradi, Federico, de Croon, Guido, Danielescu, Andreea, Daram, Anurag, Davies, Mike, Demirag, Yigit, Eshraghian, Jason, Fischer, Tobias, Forest, Jeremy, Fra, Vittorio, Furber, Steve, Furlong, P. Michael, Gilpin, William, Gilra, Aditya, Gonzalez, Hector A., Indiveri, Giacomo, Joshi, Siddharth, Karia, Vedant, Khacef, Lyes, Knight, James C., Kriener, Laura, Kubendran, Rajkumar, Kudithipudi, Dhireesha, Liu, Yao-Hong, Liu, Shih-Chii, Ma, Haoyuan, Manohar, Rajit, Margarit-Taulé, Josep Maria, Mayr, Christian, Michmizos, Konstantinos, Muir, Dylan, Neftci, Emre, Nowotny, Thomas, Ottati, Fabrizio, Ozcelikkale, Ayca, Panda, Priyadarshini, Park, Jongkil, Payvand, Melika, Pehle, Christian, Petrovici, Mihai A., Posch, Christoph, Renner, Alpha, Sandamirskaya, Yulia, Schaefer, Clemens JS, van Schaik, André, Schemmel, Johannes, Schmidgall, Samuel, Schuman, Catherine, Seo, Jae-sun, Sheik, Sadique, Shrestha, Sumit Bam, Sifalakis, Manolis, Sironi, Amos, Stewart, Matthew, Stewart, Kenneth, Stewart, Terrence C., Timcheck, Jonathan, Tömen, Nergis, Urgese, Gianvito, Verhelst, Marian, Vineyard, Craig M., Vogginger, Bernhard, Yousefzadeh, Amirreza, Zohora, Fatima Tuz, Frenkel, Charlotte, Reddi, Vijay Janapa
Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accu
Externí odkaz:
http://arxiv.org/abs/2304.04640
Autor:
Prakash, Shvetank, Stewart, Matthew, Banbury, Colby, Mazumder, Mark, Warden, Pete, Plancher, Brian, Reddi, Vijay Janapa
The sustained growth of carbon emissions and global waste elicits significant sustainability concerns for our environment's future. The growing Internet of Things (IoT) has the potential to exacerbate this issue. However, an emerging area known as Ti
Externí odkaz:
http://arxiv.org/abs/2301.11899
Autor:
Warden, Pete, Stewart, Matthew, Plancher, Brian, Banbury, Colby, Prakash, Shvetank, Chen, Emma, Asgar, Zain, Katti, Sachin, Reddi, Vijay Janapa
Machine learning sensors represent a paradigm shift for the future of embedded machine learning applications. Current instantiations of embedded machine learning (ML) suffer from complex integration, lack of modularity, and privacy and security conce
Externí odkaz:
http://arxiv.org/abs/2206.03266
Autor:
PRAKASH, SHVETANK1, STEWART, MATTHEW2, BANBURY, COLBY1, MAZUMDER, MARK1, WARDEN, PETE3, PLANCHER, BRIAN4, REDDI, VIJAY JANAPA5
Publikováno v:
Communications of the ACM. Nov2023, Vol. 66 Issue 11, p68-77. 10p.
Autor:
Warden, Pete1 pete@petewarden.com, Stewart, Matthew2 matthew_stewart@g.harvard.edu, Plancher, Brian3 bplancher@barnard.edu, Katti, Sachin4 skatti@stanford.edu, Reddi, Vijay Janapa5 vj@eecs.harvard.edu
Publikováno v:
Communications of the ACM. Nov2023, Vol. 66 Issue 11, p25-28. 4p.