Email: nick11roberts [at] cs [dot] wisc [dot] edu
Office: CS Dept. 5384, 1210 W Dayton St, Madison, WI 53706
Email: nick11roberts [at] cs [dot] wisc [dot] edu
Office: CS Dept. 5384, 1210 W Dayton St, Madison, WI 53706
Generative Modeling Helps Weak Supervision (and Vice Versa)
Benedikt Boecking, Willie Neiswanger, Nicholas Roberts, Stefano Ermon, Frederic Sala, Artur Dubrawski.
Under review.
[arXiv]
NAS-Bench-360: Benchmarking Diverse Tasks for Neural Architecture Search
Renbo Tu, Mikhail Khodak, Nicholas Roberts, Ameet Talwalkar.
Under review.
[arXiv]
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, ..., Nicholas Roberts (82), ..., (125 authors).
Preprint.
[arXiv]
[Code]
Universalizing Weak Supervision
Changho Shin, Winfred Li, Harit Vishwakarma, Nicholas Roberts, Frederic Sala.
ICLR 2022.
[arXiv]
Rethinking Neural Operations for Diverse Tasks
Nicholas Roberts*, Mikhail Khodak*, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar.
NeurIPS 2021.
[arXiv]
[Code]
[Software Package]
[Talk]
Preliminary version: Searching for Convolutions and a More Ambitious NAS
Nicholas Roberts*, Mikhail Khodak*, Tri Dao, Liam Li, Maria-Florina Balcan, Christopher Ré, Ameet Talwalkar.
Plenary Talk: AAAI 2021 Workshop on Learning Network Architecture During Training.
Decoding and Diversity in Machine Translation
Nicholas Roberts, Davis Liang, Graham Neubig, Zachary C. Lipton.
NeurIPS 2020 Resistance AI Workshop.
[arXiv]
A Simple Setting for Understanding Neural Architecture Search with Weight-Sharing
Mikhail Khodak, Liam Li, Nicholas Roberts, Maria-Florina Balcan, Ameet Talwalkar.
ICML 2020 AutoML Workshop.
[Paper]
Weight-Sharing Beyond Neural Architecture Search: Efficient Feature Map Selection and Federated Hyperparameter Tuning
Mikhail Khodak*, Liam Li*, Nicholas Roberts, Maria-Florina Balcan, Ameet Talwalkar.
MLSys 2020 On-Device Intelligence Workshop.
[Paper]
Deep Connectomics Networks: Neural Network Architectures Inspired by Neuronal Networks
Nicholas Roberts, Dian Ang Yap, Vinay U. Prabhu.
NeurIPS 2019 Real Neurons and Hidden Units Workshop.
[arXiv]
Using Deep Siamese Neural Networks to Speed up Natural Products Research
Nicholas Roberts, Poornav S. Purushothama, Vishal T. Vasudevan, Siddarth Ravichandran, Chen Zhang, William H. Gerwick, Garrison W. Cottrell.
NeurIPS 2019 workshop on Machine Learning and the Physical Sciences.
[Paper]
Grassmannian Packings in Neural Networks: Learning with Maximal Subspace Packings for Diversity and Anti-Sparsity
Dian Ang Yap, Nicholas Roberts, Vinay U. Prabhu.
NeurIPS 2019 workshop on Bayesian Deep Learning.
NeurIPS 2019 workshop on Information Theory and Machine Learning.
[arXiv]
Model Weight Theft With Just Noise Inputs: The Curious Case of the Petulant Attacker
Nicholas Roberts, Vinay U. Prabhu, Matthew McAteer.
Spotlight: ICML 2019 workshop on Security and Privacy of Machine Learning.
[arXiv]
Learning from Discriminative Feature Feedback
Sanjoy Dasgupta, Akansha Dey, Nicholas Roberts, Sivan Sabato.
NeurIPS 2018.
[Paper]
Small Molecule Accurate Recognition Technology (SMART) to Enhance Natural Products Research
Chen Zhang*, Yerlan Idelbayev*, Nicholas Roberts, Yiwen Tao, Yashwanth Nannapaneni, Brendan M. Duggan, Jie Min, Eugene C. Lin, Erik C. Gerwick, Garrison W. Cottrell, William H. Gerwick.
Scientific Reports 2017.
[Paper]
Poster: Small Molecule Accurate Recognition Technology (SMART): A Digital Frontier to Reshape Natural Product Research
Chen Zhang*, Yerlan Idelbayev*, Nicholas Roberts (presenter), Yiwen Tao, Yashwanth Nannapaneni, Brendan M. Duggan, Jie Min, Eugene C. Lin, Erik C. Gerwick, Garrison W. Cottrell, William H. Gerwick.
Best Spotlight Presentation Award: Applied Machine Learning Days 2018.
Ph.D. Computer Science
M.S. Machine Learning
B.S. Computer Science
Mathematics minor
CSE Honors Program
Computer Science
Leon S. Peters Honors Program
research assistant
research assistant
applied scientist intern
Technologies used:
Python, PyTorch, RWTH ASR, Kaldi, AWS
ai fellow
machine learner intern
Technologies used:
Python, Keras, PyTorch, TensorFlow, MATLAB, AWS
software engineering intern
Technologies used:
Python, PyTorch, TensorFlow, Gensim, Keras
applied scientist intern
Technologies used:
Python, PyTorch
machine learning researcher
Technologies used:
Python, Tensorflow, Lasagne, Theano, SciPy
software engineering intern
Technologies used:
Scala, Java, Maven, Teradata SQL, AWS, Tensorflow, Flask
volunteer full stack developer
Technologies used:
Go, Google App Engine, gohtml, HTML5, CSS3, JavaScript
software engineering intern
Technologies used:
Python, Scrapy, Selenium, Django, MySQL, JavaScript
software engineering intern
Technologies used:
Objective-C, Cocoa Touch, Flurry Analytics
I am a Ph.D. student in CS at University of Wisconsin – Madison where I am advised by Fred Sala. Before that, I had the pleasure of working with Ameet Talwalkar and Zack Lipton during my MS at Carnegie Mellon University. As an undergraduate, I was extremely fortunate to work with both Sanjoy Dasgupta and Gary Cottrell at the University of California, San Diego. Before that, I was a community college student at Fresno City College, where I was lucky enough to learn calculus, linear algebra, AND C++ from Greg Jamison.
I am broadly interested in making machine learning more accessible and applicable to new domains. As of recent, I’ve been particularly interested in model selection and automation.
Other interests: caffeine (broadly), photography, pottery.
Extracurricular: I’m an ordained Dudeist priest so I’m pretty sure I can officiate weddings. I’m also the Head Researcher of Margarita Machine Lounge Therapy at Vacation Inc. - I encourage you to check out our selection of luxury sunscreens. My Toyota Prius is unofficially the fastest Prius at Bonneville Speedway.