• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 47 matches

• 2022
• 
  Timothy Child, Owen Sheekey, Silvia Lüscher, Saeed Fallahi, Geoffrey C. Gardner, Michael Manfra, Joshua Folk:
  A Robust Protocol for Entropy Measurement in Mesoscopic Circuits. Entropy 24(3): 417 (2022)
• 
  Josh Gardner, Ian Simon, Ethan Manilow, Curtis Hawthorne, Jesse H. Engel:
  MT3: Multi-Task Multitrack Music Transcription. ICLR 2022
• 
  Curtis Hawthorne, Ian Simon, Adam Roberts, Neil Zeghidour, Josh Gardner, Ethan Manilow, Jesse H. Engel:
  Multi-instrument Music Synthesis with Spectrogram Diffusion. CoRR abs/2206.05408 (2022)
• 
  Yusong Wu, Josh Gardner, Ethan Manilow, Ian Simon, Curtis Hawthorne, Jesse H. Engel:
  The Chamber Ensemble Generator: Limitless High-Quality MIR Data via Generative Modeling. CoRR abs/2209.14458 (2022)
• 
  Josh Gardner, Zoran Popovic, Ludwig Schmidt:
  Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation. CoRR abs/2211.12703 (2022)
• 2021
• 
  Christopher Brooks, Rebecca M. Quintana, Heeryung Choi, Chris Quintana, Timothy NeCamp, Joshua Gardner:
  Towards Culturally Relevant Personalization at Scale: Experiments with Data Science Learners. Int. J. Artif. Intell. Educ. 31(3): 516-537 (2021)
• 
  Theresa Baren, Michael Cory, Mia Friedberg, Peter Gardner, James M. Hammer, Joshua Harrington, Daniel McGinnis, Riley Waechter, Tony W. H. Wong:
  On the domination number of permutation graphs and an application to strong fixed points. Discret. Appl. Math. 288: 20-34 (2021)
• 
  Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
  Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021)
• 
  Gordon S. Blair, Richard Bassett, Lucy Bastin, Lindsay Beevers, Maribel Isabel Borrajo, Mike Brown, Sarah L. Dance, Ada Dionescu, Liz Edwards, Maria Angela Ferrario, Rob Fraser, Harriet Fraser, Simon Gardner, Peter A. Henrys, Tony Hey, Stuart Homann, Chantal Huijbers, James Hutchison, Phil Jonathan, Rob Lamb, Sophie Laurie, Amber Leeson, David Leslie, Malcolm McMillan, Vatsala Nundloll, Oluwole K. Oyebamiji, Jordan Phillipson, Vicky Pope, Rachel Prudden, Stefan Reis, Maria Salama, Faiza Samreen, Dino Sejdinovic, Will Simm, Roger Street, Lauren Thornton, Ross Towe, Joshua Vande Hey, Massimo Vieno, Joanne A. Waller, John Watkins:
  The Role of Digital Technologies in Responding to the Grand Challenges of the Natural Environment: The Windermere Accord. Patterns 2(1): 100156 (2021)
• 
  Josh Gardner, Ian Simon, Ethan Manilow, Curtis Hawthorne, Jesse H. Engel:
  MT3: Multi-Task Multitrack Music Transcription. CoRR abs/2111.03017 (2021)
• 2020
• 
  Ritchie Lee, Ole J. Mengshoel, Anshu Saksena, Ryan W. Gardner, Daniel Genin, Joshua Silbermann, Michael P. Owen, Mykel J. Kochenderfer:
  Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning. J. Artif. Intell. Res. 69: 1165-1201 (2020)
• 
  Josh Gardner, Jawad Mroueh, Natalia Jenuwine, Noah Weaverdyck, Samuel Krassenstein, Arya Farahi, Danai Koutra:
  Driving with Data in the Motor City: Understanding and Predicting Fleet Maintenance Patterns. DSAA 2020: 380-389
• 
  Joshua Gardner, Shatha F. Al-Maliki, Evelyne Lutton, François Boué, Franck P. Vidal:
  Recognising Specific Foods in MRI Scans Using CNN and Visualisation. CGVC 2020: 11-18
• 
  Josh Gardner, Jawad Mroueh, Natalia Jenuwine, Noah Weaverdyck, Samuel Krassenstein, Arya Farahi, Danai Koutra:
  Driving with Data in the Motor City: Mining and Modeling Vehicle Fleet Maintenance Data. CoRR abs/2002.10010 (2020)
• 2019
• 
  Steven Gardner, Oleg Golovidov, Joshua Griffin, Patrick Koch, Wayne Thompson, Brett Wujek, Yan Xu:
  Constrained Multi-Objective Optimization for Automated Machine Learning. DSAA 2019: 364-373
• 
  Josh Gardner, Yuming Yang, Ryan S. Baker, Christopher Brooks:
  Modeling and Experimental Design for MOOC Dropout Prediction: A Replication Perspective. EDM 2019
• 
  Josh Gardner, Christopher Brooks, Ryan Baker:
  Evaluating the Fairness of Predictive Student Models Through Slicing Analysis. LAK 2019: 225-234
• 
  Timothy NeCamp, Josh Gardner, Christopher Brooks:
  Beyond A/B Testing: Sequential Randomization for Developing Interventions in Scaled Digital Learning Environments. LAK 2019: 539-548
• 
  Steven Gardner, Oleg Golovidov, Joshua Griffin, Patrick Koch, Wayne Thompson, Brett Wujek, Yan Xu:
  Constrained Multi-Objective Optimization for Automated Machine Learning. CoRR abs/1908.04909 (2019)
• 
  Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
  Advances and Open Problems in Federated Learning. CoRR abs/1912.04977 (2019)
• 2018
• 
  Joshua Patrick Gardner, Christopher Brooks:
  Evaluating Predictive Models of Student Success: Closing the Methodological Gap. J. Learn. Anal. 5(2): 105-125 (2018)
• 
  Joshua Patrick Gardner, Christopher Brooks, Warren Li:
  Learn From Your (Markov) Neighbor: Coenrollment, Assortativity, and Grade Prediction in Undergraduate Courses. J. Learn. Anal. 5(3) (2018)
• 
  Josh Gardner, Christopher Brooks:
  Student success prediction in MOOCs. User Model. User Adapt. Interact. 28(2): 127-203 (2018)
• 
  Josh Gardner, Christopher Brooks:
  Dropout Model Evaluation in MOOCs. AAAI 2018: 7906-7912
• 
  Josh Gardner, Christopher Brooks, Juan Miguel L. Andres, Ryan S. Baker:
  MORF: A Framework for Predictive Modeling and Replication At Scale With Privacy-Restricted MOOC Data. IEEE BigData 2018: 3235-3244
• 
  Christopher Brooks, Josh Gardner, Kaifeng Chen:
  How Gender Cues in Educational Video Impact Participation and Retention. ICLS 2018
• 
  Patrick Koch, Oleg Golovidov, Steven Gardner, Brett Wujek, Joshua Griffin, Yan Xu:
  Autotune: A Derivative-free Optimization Framework for Hyperparameter Tuning. KDD 2018: 443-452
• 
  Josh Gardner, Christopher Brooks:
  Coenrollment networks and their relationship to grades in undergraduate education. LAK 2018: 295-304
• 
  Josh Gardner, Christopher Brooks, Juan Miguel L. Andres, Ryan Baker:
  Replicating MOOC predictive models at scale. L@S 2018: 1:1-1:10
• 
  Josh Gardner, Christopher Brooks, Juan Miguel L. Andres, Ryan S. Baker:
  MORF: A Framework for MOOC Predictive Modeling and Replication At Scale. CoRR abs/1801.05236 (2018)

skipping 17 more matches