Search Results - "Dahl, George E"

Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships by Ma, Junshui, Sheridan, Robert P, Liaw, Andy, Dahl, George E, Svetnik, Vladimir

“…Neural networks were widely used for quantitative structure–activity relationships (QSAR) in the 1990s. Because of various practical issues (e.g., slow on…”
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Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error by Faber, Felix A, Hutchison, Luke, Huang, Bing, Gilmer, Justin, Schoenholz, Samuel S, Dahl, George E, Vinyals, Oriol, Kearnes, Steven, Riley, Patrick F, von Lilienfeld, O. Anatole

“…We investigate the impact of choosing regressors and molecular representations for the construction of fast machine learning (ML) models of 13 electronic…”
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Machine learning guided aptamer refinement and discovery by Bashir, Ali, Yang, Qin, Wang, Jinpeng, Hoyer, Stephan, Chou, Wenchuan, McLean, Cory, Davis, Geoff, Gong, Qiang, Armstrong, Zan, Jang, Junghoon, Kang, Hui, Pawlosky, Annalisa, Scott, Alexander, Dahl, George E., Berndl, Marc, Dimon, Michelle, Ferguson, B. Scott

“…Aptamers are single-stranded nucleic acid ligands that bind to target molecules with high affinity and specificity. They are typically discovered by searching…”
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Acoustic Modeling Using Deep Belief Networks by Mohamed, Abdel-rahman, Dahl, George E., Hinton, Geoffrey

“…Gaussian mixture models are currently the dominant technique for modeling the emission distribution of hidden Markov models for speech recognition. We show…”
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Artificial Intelligence-Based Breast Cancer Nodal Metastasis Detection: Insights Into the Black Box for Pathologists by Liu, Yun, Kohlberger, Timo, Norouzi, Mohammad, Dahl, George E, Smith, Jenny L, Mohtashamian, Arash, Olson, Niels, Peng, Lily H, Hipp, Jason D, Stumpe, Martin C

“…Nodal metastasis of a primary tumor influences therapy decisions for a variety of cancers. Histologic identification of tumor cells in lymph nodes can be…”
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Large-scale malware classification using random projections and neural networks by Dahl, George E., Stokes, Jack W., Li Deng, Dong Yu

“…Automatically generated malware is a significant problem for computer users. Analysts are able to manually investigate a small number of unknown files, but the…”
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A mobile-optimized artificial intelligence system for gestational age and fetal malpresentation assessment by Gomes, Ryan G., Vwalika, Bellington, Lee, Chace, Willis, Angelica, Sieniek, Marcin, Price, Joan T., Chen, Christina, Kasaro, Margaret P., Taylor, James A., Stringer, Elizabeth M., McKinney, Scott Mayer, Sindano, Ntazana, Dahl, George E., Goodnight, William, Gilmer, Justin, Chi, Benjamin H., Lau, Charles, Spitz, Terry, Saensuksopa, T., Liu, Kris, Tiyasirichokchai, Tiya, Wong, Jonny, Pilgrim, Rory, Uddin, Akib, Corrado, Greg, Peng, Lily, Chou, Katherine, Tse, Daniel, Stringer, Jeffrey S. A., Shetty, Shravya

“…Background Fetal ultrasound is an important component of antenatal care, but shortage of adequately trained healthcare workers has limited its adoption in…”
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Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition by Dahl, G. E., Dong Yu, Li Deng, Acero, A.

“…We propose a novel context-dependent (CD) model for large-vocabulary speech recognition (LVSR) that leverages recent advances in using deep belief networks for…”
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Improving deep neural networks for LVCSR using rectified linear units and dropout by Dahl, George E., Sainath, Tara N., Hinton, Geoffrey E.

“…Recently, pre-trained deep neural networks (DNNs) have outperformed traditional acoustic models based on Gaussian mixture models (GMMs) on a variety of large…”
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Large vocabulary continuous speech recognition with context-dependent DBN-HMMS by Dahl, George E., Dong Yu, Li Deng, Acero, Alex

“…The context-independent deep belief network (DBN) hidden Markov model (HMM) hybrid architecture has recently achieved promising results for phone recognition…”
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Acoustic Modeling Using Deep Belief Networks : Deep Learning for Speech and Language Processing by MOHAMED, Abdel-Rahman, DAHL, George E, HINTON, Geoffrey

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Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition : Deep Learning for Speech and Language Processing by DAHL, George E, DONG YU, LI DENG, ACERO, Alex

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Improvements to Deep Convolutional Neural Networks for LVCSR by Sainath, Tara N., Kingsbury, Brian, Mohamed, Abdel-rahman, Dahl, George E., Saon, George, Soltau, Hagen, Beran, Tomas, Aravkin, Aleksandr Y., Ramabhadran, Bhuvana

“…Deep Convolutional Neural Networks (CNNs) are more powerful than Deep Neural Networks (DNN), as they are able to better reduce spectral variation in the input…”
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What Will it Take to Fix Benchmarking in Natural Language Understanding? by Bowman, Samuel R, Dahl, George E

“…Evaluation for many natural language understanding (NLU) tasks is broken: Unreliable and biased systems score so highly on standard benchmarks that there is…”
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Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach by Ariafar, Setareh, Gilmer, Justin, Nado, Zachary, Snoek, Jasper, Jenatton, Rodolphe, Dahl, George E

“…Black box optimization requires specifying a search space to explore for solutions, e.g. a d-dimensional compact space, and this choice is critical for getting…”
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Pre-training helps Bayesian optimization too by Wang, Zi, Dahl, George E, Swersky, Kevin, Lee, Chansoo, Mariet, Zelda, Nado, Zachary, Gilmer, Justin, Snoek, Jasper, Ghahramani, Zoubin

“…Bayesian optimization (BO) has become a popular strategy for global optimization of many expensive real-world functions. Contrary to a common belief that BO is…”
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Faster Neural Network Training with Data Echoing by Choi, Dami, Passos, Alexandre, Shallue, Christopher J, Dahl, George E

“…In the twilight of Moore's law, GPUs and other specialized hardware accelerators have dramatically sped up neural network training. However, earlier stages of…”
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A Large Batch Optimizer Reality Check: Traditional, Generic Optimizers Suffice Across Batch Sizes by Nado, Zachary, Gilmer, Justin M, Shallue, Christopher J, Anil, Rohan, Dahl, George E

“…Recently the LARS and LAMB optimizers have been proposed for training neural networks faster using large batch sizes. LARS and LAMB add layer-wise…”
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Pre-trained Gaussian Processes for Bayesian Optimization by Wang, Zi, Dahl, George E, Swersky, Kevin, Lee, Chansoo, Nado, Zachary, Gilmer, Justin, Snoek, Jasper, Ghahramani, Zoubin

“…Journal of Machine Learning Research, 25(212):1-83, 2024. URL http://jmlr.org/papers/v25/23-0269.html Bayesian optimization (BO) has become a popular strategy…”
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Adaptive Gradient Methods at the Edge of Stability by Cohen, Jeremy M, Ghorbani, Behrooz, Krishnan, Shankar, Agarwal, Naman, Medapati, Sourabh, Badura, Michal, Suo, Daniel, Cardoze, David, Nado, Zachary, Dahl, George E, Gilmer, Justin

“…Very little is known about the training dynamics of adaptive gradient methods like Adam in deep learning. In this paper, we shed light on the behavior of these…”
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