Zobrazeno 1 - 10
of 86
pro vyhledávání: '"Prasad, Aditya A"'
Autor:
Lee, David H., Prasad, Aditya, Vuong, Ramiro Deo-Campo, Wang, Tianyu, Han, Eric, Kempe, David
Dynamic programming (DP) is a fundamental and powerful algorithmic paradigm taught in most undergraduate (and many graduate) algorithms classes. DP problems are challenging for many computer science students because they require identifying unique pr
Externí odkaz:
http://arxiv.org/abs/2411.07705
Autor:
Shen, Yikang, Stallone, Matthew, Mishra, Mayank, Zhang, Gaoyuan, Tan, Shawn, Prasad, Aditya, Soria, Adriana Meza, Cox, David D., Panda, Rameswar
Finding the optimal learning rate for language model pretraining is a challenging task. This is not only because there is a complicated correlation between learning rate, batch size, number of training tokens, model size, and other hyperparameters bu
Externí odkaz:
http://arxiv.org/abs/2408.13359
Autor:
Stallone, Matt, Saxena, Vaibhav, Karlinsky, Leonid, McGinn, Bridget, Bula, Tim, Mishra, Mayank, Soria, Adriana Meza, Zhang, Gaoyuan, Prasad, Aditya, Shen, Yikang, Surendran, Saptha, Guttula, Shanmukha, Patel, Hima, Selvam, Parameswaran, Dang, Xuan-Hong, Koyfman, Yan, Sood, Atin, Feris, Rogerio, Desai, Nirmit, Cox, David D., Puri, Ruchir, Panda, Rameswar
This paper introduces long-context Granite code models that support effective context windows of up to 128K tokens. Our solution for scaling context length of Granite 3B/8B code models from 2K/4K to 128K consists of a light-weight continual pretraini
Externí odkaz:
http://arxiv.org/abs/2407.13739
Autor:
Gershon, Talia, Seelam, Seetharami, Belgodere, Brian, Bonilla, Milton, Hoang, Lan, Barnett, Danny, Chung, I-Hsin, Mohan, Apoorve, Chen, Ming-Hung, Luo, Lixiang, Walkup, Robert, Evangelinos, Constantinos, Salaria, Shweta, Dombrowa, Marc, Park, Yoonho, Kayi, Apo, Schour, Liran, Alim, Alim, Sydney, Ali, Maniotis, Pavlos, Schares, Laurent, Metzler, Bernard, Karacali-Akyamac, Bengi, Wen, Sophia, Chiba, Tatsuhiro, Choochotkaew, Sunyanan, Yoshimura, Takeshi, Misale, Claudia, Elengikal, Tonia, Connor, Kevin O, Liu, Zhuoran, Molina, Richard, Schneidenbach, Lars, Caden, James, Laibinis, Christopher, Fonseca, Carlos, Tarasov, Vasily, Sundararaman, Swaminathan, Schmuck, Frank, Guthridge, Scott, Cohn, Jeremy, Eshel, Marc, Muench, Paul, Liu, Runyu, Pointer, William, Wyskida, Drew, Krull, Bob, Rose, Ray, Wolfe, Brent, Cornejo, William, Walter, John, Malone, Colm, Perucci, Clifford, Franco, Frank, Hinds, Nigel, Calio, Bob, Druyan, Pavel, Kilduff, Robert, Kienle, John, McStay, Connor, Figueroa, Andrew, Connolly, Matthew, Fost, Edie, Roma, Gina, Fonseca, Jake, Levy, Ido, Payne, Michele, Schenkel, Ryan, Malki, Amir, Schneider, Lion, Narkhede, Aniruddha, Moshref, Shekeba, Kisin, Alexandra, Dodin, Olga, Rippon, Bill, Wrieth, Henry, Ganci, John, Colino, Johnny, Habeger-Rose, Donna, Pandey, Rakesh, Gidh, Aditya, Gaur, Aditya, Patterson, Dennis, Salmani, Samsuddin, Varma, Rambilas, Rumana, Rumana, Sharma, Shubham, Mishra, Mayank, Panda, Rameswar, Prasad, Aditya, Stallone, Matt, Zhang, Gaoyuan, Shen, Yikang, Cox, David, Puri, Ruchir, Agrawal, Dakshi, Thorstensen, Drew, Belog, Joel, Tang, Brent, Gupta, Saurabh Kumar, Biswas, Amitabha, Maheshwari, Anup, Gampel, Eran, Van Patten, Jason, Runion, Matthew, Kaki, Sai, Bogin, Yigal, Reitz, Brian, Pritko, Steve, Najam, Shahan, Nambala, Surya, Chirra, Radhika, Welp, Rick, DiMitri, Frank, Telles, Felipe, Arvelo, Amilcar, Chu, King, Seminaro, Ed, Schram, Andrew, Eickhoff, Felix, Hanson, William, Mckeever, Eric, Joseph, Dinakaran, Chaudhary, Piyush, Shivam, Piyush, Chaudhary, Puneet, Jones, Wesley, Guthrie, Robert, Bostic, Chris, Islam, Rezaul, Duersch, Steve, Sawdon, Wayne, Lewars, John, Klos, Matthew, Spriggs, Michael, McMillan, Bill, Gao, George, Kamra, Ashish, Singh, Gaurav, Curry, Marc, Katarki, Tushar, Talerico, Joe, Shi, Zenghui, Malleni, Sai Sindhur, Gallen, Erwan
AI Infrastructure plays a key role in the speed and cost-competitiveness of developing and deploying advanced AI models. The current demand for powerful AI infrastructure for model training is driven by the emergence of generative AI and foundational
Externí odkaz:
http://arxiv.org/abs/2407.05467
Autor:
Mishra, Mayank, Stallone, Matt, Zhang, Gaoyuan, Shen, Yikang, Prasad, Aditya, Soria, Adriana Meza, Merler, Michele, Selvam, Parameswaran, Surendran, Saptha, Singh, Shivdeep, Sethi, Manish, Dang, Xuan-Hong, Li, Pengyuan, Wu, Kun-Lung, Zawad, Syed, Coleman, Andrew, White, Matthew, Lewis, Mark, Pavuluri, Raju, Koyfman, Yan, Lublinsky, Boris, de Bayser, Maximilien, Abdelaziz, Ibrahim, Basu, Kinjal, Agarwal, Mayank, Zhou, Yi, Johnson, Chris, Goyal, Aanchal, Patel, Hima, Shah, Yousaf, Zerfos, Petros, Ludwig, Heiko, Munawar, Asim, Crouse, Maxwell, Kapanipathi, Pavan, Salaria, Shweta, Calio, Bob, Wen, Sophia, Seelam, Seetharami, Belgodere, Brian, Fonseca, Carlos, Singhee, Amith, Desai, Nirmit, Cox, David D., Puri, Ruchir, Panda, Rameswar
Large Language Models (LLMs) trained on code are revolutionizing the software development process. Increasingly, code LLMs are being integrated into software development environments to improve the productivity of human programmers, and LLM-based age
Externí odkaz:
http://arxiv.org/abs/2405.04324
We study the combinatorial contract design problem, introduced and studied by Dutting et. al. (2021, 2022), in both the single and multi-agent settings. Prior work has examined the problem when the principal's utility function is submodular in the ac
Externí odkaz:
http://arxiv.org/abs/2308.07473
Autor:
Martie, Lee, Rosenberg, Jessie, Demers, Veronique, Zhang, Gaoyuan, Bhardwaj, Onkar, Henning, John, Prasad, Aditya, Stallone, Matt, Lee, Ja Young, Yip, Lucy, Adesina, Damilola, Paikari, Elahe, Resendiz, Oscar, Shaw, Sarah, Cox, David
Publikováno v:
2023 IEEE/ACM 45th International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER), Melbourne, Australia, 2023, pp. (forthcoming)
Compositional AI systems, which combine multiple artificial intelligence components together with other application components to solve a larger problem, have no known pattern of development and are often approached in a bespoke and ad hoc style. Thi
Externí odkaz:
http://arxiv.org/abs/2302.05941
Autor:
Prasad, Aditya A
Microgrids could be the answer to integrating distributed energy resources into our power grid. It promises improved resilience, reliability, efficiency, and decarbonizing of our electric grid. This paper models a low voltage direct current microgrid
Externí odkaz:
http://arxiv.org/abs/2107.12474
We propose a particle-based method to simulate thin-film fluid that jointly facilitates aggressive surface deformation and vigorous tangential flows. We build our dynamics model from the surface tension driven Navier-Stokes equation with the dimensio
Externí odkaz:
http://arxiv.org/abs/2105.07656
Autor:
Iyer, Akshay, Zhang, Yichi, Prasad, Aditya, Tao, Siyu, Wang, Yixing, Schadler, Linda, Brinson, L Catherine, Chen, Wei
Materials design can be cast as an optimization problem with the goal of achieving desired properties, by varying material composition, microstructure morphology, and processing conditions. Existence of both qualitative and quantitative material desi
Externí odkaz:
http://arxiv.org/abs/1907.02577