Zobrazeno 1 - 10
of 791
pro vyhledávání: '"Dixon, Matthew A."'
Autor:
Koch, Luke, Oesch, Sean, Chaulagain, Amul, Dixon, Jared, Dixon, Matthew, Huettal, Mike, Sadovnik, Amir, Watson, Cory, Weber, Brian, Hartman, Jacob, Patulski, Richard
A polyglot is a file that is valid in two or more formats. Polyglot files pose a problem for malware detection systems that route files to format-specific detectors/signatures, as well as file upload and sanitization tools. In this work we found that
Externí odkaz:
http://arxiv.org/abs/2407.01529
Autor:
Abdin, Marah, Aneja, Jyoti, Awadalla, Hany, Awadallah, Ahmed, Awan, Ammar Ahmad, Bach, Nguyen, Bahree, Amit, Bakhtiari, Arash, Bao, Jianmin, Behl, Harkirat, Benhaim, Alon, Bilenko, Misha, Bjorck, Johan, Bubeck, Sébastien, Cai, Martin, Cai, Qin, Chaudhary, Vishrav, Chen, Dong, Chen, Dongdong, Chen, Weizhu, Chen, Yen-Chun, Chen, Yi-Ling, Cheng, Hao, Chopra, Parul, Dai, Xiyang, Dixon, Matthew, Eldan, Ronen, Fragoso, Victor, Gao, Jianfeng, Gao, Mei, Gao, Min, Garg, Amit, Del Giorno, Allie, Goswami, Abhishek, Gunasekar, Suriya, Haider, Emman, Hao, Junheng, Hewett, Russell J., Hu, Wenxiang, Huynh, Jamie, Iter, Dan, Jacobs, Sam Ade, Javaheripi, Mojan, Jin, Xin, Karampatziakis, Nikos, Kauffmann, Piero, Khademi, Mahoud, Kim, Dongwoo, Kim, Young Jin, Kurilenko, Lev, Lee, James R., Lee, Yin Tat, Li, Yuanzhi, Li, Yunsheng, Liang, Chen, Liden, Lars, Lin, Xihui, Lin, Zeqi, Liu, Ce, Liu, Liyuan, Liu, Mengchen, Liu, Weishung, Liu, Xiaodong, Luo, Chong, Madan, Piyush, Mahmoudzadeh, Ali, Majercak, David, Mazzola, Matt, Mendes, Caio César Teodoro, Mitra, Arindam, Modi, Hardik, Nguyen, Anh, Norick, Brandon, Patra, Barun, Perez-Becker, Daniel, Portet, Thomas, Pryzant, Reid, Qin, Heyang, Radmilac, Marko, Ren, Liliang, de Rosa, Gustavo, Rosset, Corby, Roy, Sambudha, Ruwase, Olatunji, Saarikivi, Olli, Saied, Amin, Salim, Adil, Santacroce, Michael, Shah, Shital, Shang, Ning, Sharma, Hiteshi, Shen, Yelong, Shukla, Swadheen, Song, Xia, Tanaka, Masahiro, Tupini, Andrea, Vaddamanu, Praneetha, Wang, Chunyu, Wang, Guanhua, Wang, Lijuan, Wang, Shuohang, Wang, Xin, Wang, Yu, Ward, Rachel, Wen, Wen, Witte, Philipp, Wu, Haiping, Wu, Xiaoxia, Wyatt, Michael, Xiao, Bin, Xu, Can, Xu, Jiahang, Xu, Weijian, Xue, Jilong, Yadav, Sonali, Yang, Fan, Yang, Jianwei, Yang, Yifan, Yang, Ziyi, Yu, Donghan, Yuan, Lu, Zhang, Chenruidong, Zhang, Cyril, Zhang, Jianwen, Zhang, Li Lyna, Zhang, Yi, Zhang, Yue, Zhang, Yunan, Zhou, Xiren
We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal testing, rivals that of models such as Mixtral 8x7B and GPT-3.5 (e.g., phi
Externí odkaz:
http://arxiv.org/abs/2404.14219
Publikováno v:
Short Communication: Beyond Surrogate Modeling: Learning the Local Volatility via Shape Constraints, SIAM Journal on Financial Mathematics 12(3), SC58-SC69, 2021
We explore the abilities of two machine learning approaches for no-arbitrage interpolation of European vanilla option prices, which jointly yield the corresponding local volatility surface: a finite dimensional Gaussian process (GP) regression approa
Externí odkaz:
http://arxiv.org/abs/2212.09957
Publikováno v:
Harvard Business Review. Nov/Dec2023, Vol. 101 Issue 6, p72-81. 10p. 1 Color Photograph, 1 Chart, 1 Graph.
We use deep partial least squares (DPLS) to estimate an asset pricing model for individual stock returns that exploits conditioning information in a flexible and dynamic way while attributing excess returns to a small set of statistical risk factors.
Externí odkaz:
http://arxiv.org/abs/2206.10014
Catastrophe (CAT) bond markets are incomplete and hence carry uncertainty in instrument pricing. As such various pricing approaches have been proposed, but none treat the uncertainty in catastrophe occurrences and interest rates in a sufficiently fle
Externí odkaz:
http://arxiv.org/abs/2205.04520
Autor:
Klocek, Sylwester, Dong, Haiyu, Dixon, Matthew, Kanengoni, Panashe, Kazmi, Najeeb, Luferenko, Pete, Lv, Zhongjian, Sharma, Shikhar, Weyn, Jonathan, Xiang, Siqi
Publikováno v:
NeurIPS 2021 Workshop on Tackling Climate Change with Machine Learning, 2021. https://www.climatechange.ai/papers/neurips2021/19
We present the encoder-forecaster convolutional long short-term memory (LSTM) deep-learning model that powers Microsoft Weather's operational precipitation nowcasting product. This model takes as input a sequence of weather radar mosaics and determin
Externí odkaz:
http://arxiv.org/abs/2111.09954
Autor:
Lauscher, Johannes C., Dixon, Matthew E.B., Jada, George, Afshin, Mariam, Neumann, Konrad, Cheung, Helen, Martel, Guillaume, Hallet, Julie, Coburn, Natalie, Law, Calvin, Milot, Laurent, Karanicolas, Paul J.
Publikováno v:
In HPB June 2024 26(6):782-788
Autor:
Mutono, Nyamai *, *, Basáñez, Maria-Gloria *, James, Ananthu, Stolk, Wilma A, Makori, Anita, Kimani, Teresia Njoki, Hollingsworth, T Déirdre, Vasconcelos, Andreia, Dixon, Matthew A, de Vlas, Sake J, Thumbi, S M
Publikováno v:
In The Lancet Global Health May 2024 12(5):e771-e782
Autor:
Olecki, Elizabeth J., Perez Holguin, Rolfy A., Mayhew, Mackenzie M., Wong, William G., Vining, Charles C., Peng, June S., Shen, Chan, Dixon, Matthew E.B.
Publikováno v:
In Journal of Surgical Research February 2024 294:160-168