Josh Gardner

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All published works

Action	Title	Year	Authors
+ PDF Chat	DataComp-LM: In search of the next generation of training sets for language models	2024	Jeffrey Li Alex Chengyu Fang Georgios Smyrnis Maor Ivgi Matt Jordan Samir Yitzhak Gadre Hritik Bansal Etash Guha Sedrick Scott Keh Kushal Arora
+ PDF Chat	Large Scale Transfer Learning for Tabular Data via Language Modeling	2024	Josh Gardner Juan C. Perdomo Ludwig Schmidt
+	VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use	2023	Yonatan Bitton Hritik Bansal Jack Hessel Rulin Shao Wanrong Zhu Anas Awadalla Josh Gardner Rohan Taori Ludwig Schimdt
+	OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models	2023	Anas Awadalla Irena Gao Josh Gardner Jack Hessel Yusuf Hanafy Wanrong Zhu Kalyani Marathe Yonatan Bitton Samir Yitzhak Gadre Shiori Sagawa
+	LLark: A Multimodal Foundation Model for Music	2023	Josh Gardner Simon Durand Daniel Stoller Rachel Bittner
+	Benchmarking Distribution Shift in Tabular Data with TableShift	2023	Josh Gardner Zoran Popović Ludwig Schmidt
+	Multi-instrument Music Synthesis with Spectrogram Diffusion	2022	Curtis Hawthorne Ian Simon Adam Roberts Neil Zeghidour Josh Gardner Ethan Manilow Jesse Engel
+	The Chamber Ensemble Generator: Limitless High-Quality MIR Data via Generative Modeling	2022	Yusong Wu Josh Gardner Ethan Manilow Ian Simon Curtis Hawthorne Jesse Engel
+	Subgroup Robustness Grows On Trees: An Empirical Baseline Investigation	2022	Josh Gardner Zoran Popović Ludwig Schmidt
+	MT3: Multi-Task Multitrack Music Transcription	2021	Josh Gardner Ian Simon Ethan Manilow Curtis Hawthorne Jesse Engel
+ PDF Chat	MT3: Multi-Task Multitrack Music Transcription	2021	Josh Gardner Ian Simon Ethan Manilow Curtis Hawthorne Jesse Engel
+ PDF Chat	Advances and Open Problems in Federated Learning	2021	Peter Kairouz H. Brendan McMahan Brendan Avent Aurélien Bellet Mehdi Bennis Arjun Nitin Bhagoji Kallista Bonawitz Zachary Charles Graham Cormode Rachel Cummings
+	MT3: Multi-Task Multitrack Music Transcription	2021	Josh Gardner Ian Simon Ethan Manilow Curtis Hawthorne Jesse Engel
+	Driving with Data in the Motor City: Understanding and Predicting Fleet Maintenance Patterns	2020	Josh Gardner Jawad Mroueh Natalia Jenuwine Noah Waverdyck Samuel Krassenstein Arya Farahi Danai Koutra
+	Driving with Data in the Motor City: Mining and Modeling Vehicle Fleet Maintenance Data	2020	Josh Gardner Jawad Mroueh Natalia Jenuwine N. Weaverdyck Samuel Krassenstein Arya Farahi Danai Koutra
+	Driving with Data in the Motor City: Mining and Modeling Vehicle Fleet Maintenance Data	2020	Josh Gardner Jawad Mroueh Natalia Jenuwine N. Weaverdyck Samuel Krassenstein Arya Farahi Danai Koutra
+ PDF Chat	Beyond A/B Testing: Sequential Randomization for Developing Interventions in Scaled Digital Learning Environments	2019	Timothy NeCamp Josh Gardner Christopher Brooks
+ PDF Chat	Beyond A/B Testing	2019	Timothy NeCamp Josh Gardner Christopher Brooks
+ PDF Chat	MORF: A Framework for Predictive Modeling and Replication At Scale With Privacy-Restricted MOOC Data	2018	Josh Gardner Christopher Brooks Juan Andrés Ryan S. Baker
+ PDF Chat	Beyond A/B Testing: Sequential Randomization for Developing Interventions in Scaled Digital Learning Environments	2018	Timothy NeCamp Josh Gardner Christopher Brooks
+ PDF Chat	Student success prediction in MOOCs	2018	Josh Gardner Christopher Brooks
+	Dropout Model Evaluation in MOOCs.	2018	Josh Gardner Christopher Brooks
+	Evaluating Predictive Models of Student Success: Closing the Methodological Gap	2018	Josh Gardner Christopher Brooks
+	MORF: A Framework for MOOC Predictive Modeling and Replication At Scale.	2018	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	2018	Josh Gardner Christopher Brooks Juan Miguel L. Andres Ryan S. Baker
+	Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining	2018	Josh Gardner Yuming Yang Ryan S. Baker Christopher Brooks
+	Evaluating Predictive Models of Student Success: Closing the Methodological Gap	2018	Josh Gardner Christopher Brooks
+	Dropout Model Evaluation in MOOCs	2018	Josh Gardner Christopher Brooks
+	MORF: A Framework for Predictive Modeling and Replication At Scale With Privacy-Restricted MOOC Data	2018	Josh Gardner Christopher Brooks Juan Miguel L. Andres Ryan S. Baker
+	Driving with Data: Modeling and Forecasting Vehicle Fleet Maintenance in Detroit	2017	Josh Gardner Danai Koutra Jawad Mroueh V. Pang Arya Farahi Sam Krassenstein Jared Webb

Common Coauthors

Coauthor	Papers Together
Christopher Brooks	12
Ian Simon	5
Ludwig Schmidt	5
Curtis Hawthorne	5
Ryan S. Baker	5
Ethan Manilow	5
Jesse Engel	5
Arya Farahi	4
Jawad Mroueh	4
Danai Koutra	4
Timothy NeCamp	3
Yonatan Bitton	3
Samuel Krassenstein	3
Natalia Jenuwine	3
Juan Miguel L. Andres	3
Zoran Popović	2
Hritik Bansal	2
Jenia Jitsev	2
Kalyani Marathe	2
Wanrong Zhu	2
Anas Awadalla	2
Mitchell Wortsman	2
Gabriel Ilharco	2
Rulin Shao	2
Jack Hessel	2
Samir Yitzhak Gadre	2
N. Weaverdyck	2
Pang Wei Koh	2
Rohan Taori	1
Zachary Garrett	1
Khyathi Raghavi Chandu	1
Rafael G. L. D’Oliveira	1
Badih Ghazi	1
Florian Tramèr	1
Chaoyang He	1
Prateek Mittal	1
Adrià Gascón	1
Justin Hsu	1
Phillip B. Gibbons	1
Giannis Daras	1
Ayfer Özgür	1
Graham Cormode	1
Aurélien Bellet	1
Alex Chengyu Fang	1
Aaron Gokaslan	1
Weikang Song	1
Rasmus Pagh	1
Zachary Charles	1
Brendan Avent	1
Aleksandra Korolova	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Why We (Usually) Don't Have to Worry About Multiple Comparisons	2012	Andrew Gelman Jennifer Hill Masanao Yajima	4
+	Towards Feature Engineering at Scale for Data from Massive Open Online Courses	2014	Kalyan Veeramachaneni Una-May O’Reilly Colin Taylor	4
+ PDF Chat	50 Years of Data Science	2017	David L. Donoho	4
+ PDF Chat	Sequential Multiple Assignment Randomized Trial (SMART) with Adaptive Randomization for Quality Improvement in Depression Treatment Program	2014	Ying Kuen Cheung Bibhas Chakraborty Karina W. Davidson	3
+	Recurrent Neural Network Regularization	2014	Wojciech Zaremba Ilya Sutskever Oriol Vinyals	3
+ PDF Chat	An introduction to Docker for reproducible research	2015	Carl Boettiger	3
+ PDF Chat	A "SMART" Design for Building Individualized Treatment Sequences	2012	Huitian Lei Inbal Nahum‐Shani Kevin G. Lynch David W. Oslin Susan A. Murphy	3
+	A Design for Testing Clinical Strategies: Biased Adaptive Within-Subject Randomization	2000	Phillip W. Lavori Ree Dawson	3
+ PDF Chat	The Multiphase Optimization Strategy (MOST) and the Sequential Multiple Assignment Randomized Trial (SMART)	2007	Linda M. Collins Susan A. Murphy Victor J. Strecher	3
+	Collective Sampling and Analysis of High Order Tensors for Chatroom Communications	2006	Evrim Acar Seyit Camtepe Bülent Yener	3
+ PDF Chat	Deep Reinforcement Learning That Matters	2018	Peter Henderson Riashat Islam Philip Bachman Joëlle Pineau Doina Precup David Meger	3
+	Dynamic treatment regimes: practical design considerations	2004	Philip W. Lavori Ree Dawson	3
+	Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition	1970	J. Douglas Carroll Jih-Jie Chang	3
+ PDF Chat	Efficient MATLAB Computations with Sparse and Factored Tensors	2007	Brett W. Bader Tamara G. Kolda	3
+	CubeSVD	2005	Jian-Tao Sun Hua-Jun Zeng Huan Liu Yuchang Lu Zheng Chen	3
+	Delving Deeper into MOOC Student Dropout Prediction.	2017	Jacob Whitehill Kiran Mohan Daniel Seaton Yigal Rosen Dustin Tingley	3
+	Factorization tricks for LSTM networks	2017	Oleksii Kuchaiev Boris Ginsburg	3
+ PDF Chat	Combining Difficulty Ranking with Multi-Armed Bandits to Sequence Educational Content	2018	Avi Segal Yossi Ben David Joseph Jay Williams Kobi Gal Yaar Shalom	3
+ PDF Chat	An experimental design for the development of adaptive treatment strategies	2004	Susan A. Murphy	3
+	Discussion Tracking in Enron Email Using PARAFAC	2007	Brett W. Bader Michael W. Berry Murray Browne	3
+ PDF Chat	The ASA Statement on <i>p</i>-Values: Context, Process, and Purpose	2016	Ronald L. Wasserstein Nicole A. Lazar	3
+ PDF Chat	Adaptive design methods in clinical trials – a review	2008	Shein‐Chung Chow Mark Chang	3
+	Tensor Decompositions and Applications	2009	Tamara G. Kolda Brett W. Bader	3
+	Towards automatic experimentation of educational knowledge	2014	Yun-En Liu Travis Mandel Emma Brunskill Zoran Popović	3
+	TensorSplat: Spotting Latent Anomalies in Time	2012	Danai Koutra Evangelos E. Papalexakis Christos Faloutsos	3
+ PDF Chat	Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research	2014	Daniel Almirall Inbal Nahum‐Shani Nancy E. Sherwood Susan A. Murphy	2
+	Likely to stop? Predicting Stopout in Massive Open Online Courses	2014	Colin Taylor Kalyan Veeramachaneni Una-May O’Reilly	2
+ PDF Chat	Evaluating Predictive Models of Student Success: Closing the Methodological Gap	2018	Joshua Gardner Christopher Brooks	2
+	Enabling End-To-End Machine Learning Replicability: A Case Study in Educational Data Mining	2018	Josh Gardner Yuming Yang Ryan S. Baker Christopher Brooks	2
+	Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing	1995	Yoav Benjamini Yosef Hochberg	2
+	Deep Learning in the Automotive Industry: Recent Advances and Application Examples.	2019	Kanwar Bharat Singh Mustafa Ali Arat	2
+ PDF Chat	Fairness through awareness	2012	Cynthia Dwork Moritz Hardt Toniann Pitassi Omer Reingold Richard S. Zemel	1
+ PDF Chat	Differentially Private Distributed Optimization	2015	Zhenqi Huang Sayan Mitra Nitin H. Vaidya	1
+	Explaining and Harnessing Adversarial Examples	2014	Ian Goodfellow Jonathon Shlens Christian Szegedy	1
+ PDF Chat	Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)	2001	Leo Breiman	1
+ PDF Chat	Bayesian estimation supersedes the t test.	2012	John K. Kruschke	1
+	How deep is knowledge tracing?	2016	Mohammad Khajah Robert Lindsey Michael C. Mozer	1
+	Local Privacy and Statistical Minimax Rates	2013	John C. Duchi Michael I. Jordan Martin J. Wainwright	1
+	Capturing "attrition intensifying" structural traits from didactic interaction sequences of MOOC learners	2014	Tanmay Sinha Nan Li Patrick Jermann Pierre Dillenbourg	1
+	Statistical Comparisons of Classifiers over Multiple Data Sets	2006	Janez Demšar	1
+	Mining MOOC Clickstreams: On the Relationship Between Learner Video-Watching Behavior and Performance.	2015	Christopher G. Brinton Swapna Buccapatnam Mung Chiang H. Vincent Poor	1
+	Hyperparameter optimization with approximate gradient	2016	Fabián Pedregosa	1
+	What Can We Learn Privately?	2011	Shiva Prasad Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam Smith	1
+	Topographic components model for event-related potentials and some biophysical considerations	1988	Joachim Möcks	1
+	Information-theoretic lower bounds for distributed statistical estimation with communication constraints	2013	Yuchen Zhang John C. Duchi Michael I. Jordan Martin J. Wainwright	1
+ PDF Chat	Reinforcement learning design for cancer clinical trials	2009	Yufan Zhao Michael R. Kosorok Donglin Zeng	1
+ PDF Chat	Universally utility-maximizing privacy mechanisms	2009	Arpita Ghosh Tim Roughgarden Mukund Sundararajan	1
+	Predicting Performance on MOOC Assessments using Multi-Regression Models	2016	Zhiyun Ren Huzefa Rangwala Aditya Johri	1
+ PDF Chat	Deep Learning with Differential Privacy	2016	Martı́n Abadi Andy Chu Ian Goodfellow H. Brendan McMahan Ilya Mironov Kunal Talwar Li Zhang	1
+	Multi-Armed Bandits for Intelligent Tutoring Systems	2013	Benjamin Clément Didier Roy Pierre-Yves Oudeyer Manuel Lopes	1