@inproceedings{shirzad:spexphormer, author = {Hamed Shirzad and Honghao Lin and Balaji Venkatachalam and Ameya Velingker and David Woodruff and Danica J. Sutherland}, title = {Even Sparser Graph Transformers}, year = {2024}, booktitle = {Neural Information Processing Systems (NeurIPS)}, } @inproceedings{ren:il-icl, author = {Yi Ren and Shangmin Guo and Linlu Qiu and Bailin Wang and Danica J. Sutherland}, title = {Language Model Evolution: An Iterated Learning Perspective}, year = {2024}, archivePrefix = {arXiv}, arxivId = {2404.04286}, eprint = {2404.04286}, booktitle = {Neural Information Processing Systems (NeurIPS)}, } @inproceedings{bae:maxherding, author = {Wonho Bae and Jyunhug Noh and Danica J. Sutherland}, title = {Generalized Coverage for More Robust Low-Budget Active Learning}, year = {2024}, archivePrefix = {arXiv}, arxivId = {2407.12212}, eprint = {2407.12212}, booktitle = {European Conference on Computer Vision (ECCV)}, } @inproceedings{bae:active-meta, author = {Wonho Bae and Jing Wang and Danica J. Sutherland}, title = {Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling}, year = {2024}, archivePrefix = {arXiv}, arxivId = {2311.02879}, eprint = {2311.02879}, booktitle = {European Conference on Computer Vision (ECCV)}, } @misc{ren:simplicity-ld, author = {Yi Ren and Danica J. Sutherland}, title = {Understanding Simplicity Bias towards Compositional Mappings via Learning Dynamics}, year = {2024}, archivePrefix = {arXiv}, arxivId = {2409.09626}, eprint = {2409.09626}, } @misc{xu:hsic-d, author = {Nathaniel Xu and Feng Liu and Danica J. Sutherland}, title = {Learning Deep Kernels for Non-Parametric Independence Testing}, year = {2024}, archivePrefix = {arXiv}, arxivId = {2409.06890}, eprint = {2409.06890}, } @article{yang:dp-ntk, author = {Yilin Yang and Kamil Adamczewski and Xiaoxiao Li and Danica J. Sutherland and Mijung Park}, title = {Differentially Private Neural Tangent Kernels (DP-NTK) for Privacy-Preserving Data Generation}, year = {2024}, archivePrefix = {arXiv}, arxivId = {2303.01687}, eprint = {2303.01687}, journal = {Journal of Artifical Intelligence Research}, } @article{bae:adaflood, author = {Wonho Bae and Yi Ren and Mohamad Osama Ahmed and Frederick Tung and Danica J. Sutherland and Gabriel Oliveira}, title = {AdaFlood: Adaptive Flood Regularization}, year = {2024}, archivePrefix = {arXiv}, arxivId = {2311.02891}, eprint = {2311.02891}, journal = {Transactions on Machine Learning Research}, url = {https://openreview.net/forum?id=2s5YU6CSEz}, } @inproceedings{mohamadi:grokking, author = {Mohamad Amin Mohamadi and Zhiyuan Li and Lei Wu and Danica J. Sutherland}, title = {Why Do You Grok? A Theoretical Analysis on Grokking Modular Addition}, year = {2024}, archivePrefix = {arXiv}, arxivId = {2407.12332}, eprint = {2407.12332}, booktitle = {International Conference on Machine Learning (ICML)}, } @misc{ren:llm-dynamics, author = {Yi Ren and Danica J. Sutherland}, title = {Learning Dynamics of LLM Finetuning}, year = {2024}, archivePrefix = {arXiv}, arxivId = {2407.10490}, eprint = {2407.10490}, } @inproceedings{yang:dp-ntk-workshop, author = {Yilin Yang and Kamil Adamczewski and Danica J. Sutherland and Xiaoxiao Li and Mijung Park}, title = {Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation}, year = {2024}, booktitle = {Privacy-Preserving Artificial Intelligence (AAAI workshop)}, } @misc{pogodin:split-kci, author = {Roman Pogodin and Antonin Schrab and Yazhe Li and Danica J. Sutherland and Arthur Gretton}, title = {Practical Kernel Tests of Conditional Independence}, year = {2024}, archivePrefix = {arXiv}, arxivId = {2402.13196}, eprint = {2402.13196}, } @inproceedings{shirzad:sparsifying-exphormer, author = {Hamed Shirzad and Balaji Venkatachalam and Ameya Velingker and Danica J. Sutherland and David Woodruff}, title = {Low-Width Approximations and Sparsification for Scaling Graph Transformers}, year = {2023}, booktitle = {New Frontiers in Graph Learning (NeurIPS workshop)}, } @inproceedings{mohamadi:grokking-workshop, author = {Mohamad Amin Mohamadi and Zhiyuan Li and Lei Wu and Danica J. Sutherland}, title = {Grokking modular arithmetic can be explained by margin maximization}, year = {2023}, booktitle = {Mathematics of Modern Machine Learning (NeurIPS workshop)}, } @inproceedings{ren:sem-il, author = {Yi Ren and Samuel Lavoie and Mikhail Galkin and Danica J. Sutherland and Aaron Courville}, title = {Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings}, year = {2023}, archivePrefix = {arXiv}, arxivId = {2310.18777}, eprint = {2310.18777}, booktitle = {Neural Information Processing Systems (NeurIPS)}, } @inproceedings{shirzad:exphormer, author = {Hamed Shirzad and Ameya Velingker and Balaji Venkatachalam and Danica J. Sutherland and Ali Kemal Sinop}, title = {Exphormer: Scaling Graph Transformers with Expander Graphs}, year = {2023}, archivePrefix = {arXiv}, arxivId = {2303.06147}, eprint = {2303.06147}, booktitle = {International Conference on Machine Learning (ICML)}, } @inproceedings{mohamadi:pseudo-ntk, author = {Mohamad Amin Mohamadi and Wonho Bae and Danica J. Sutherland}, title = {A Fast, Well-Founded Approximation to the Empirical Neural Tangent Kernel}, year = {2023}, archivePrefix = {arXiv}, arxivId = {2206.12543}, eprint = {2206.12543}, booktitle = {International Conference on Machine Learning (ICML)}, } @inproceedings{queerinai:qai, author = {Organizers of QueerInAI and Analeia Ovalle and Arjun Subramonian and Ashwin Singh and Claas Voelcker and Danica J. Sutherland and Davide Locatelli and Eva Breznik and Filip Klubi{\v c}ka and Hang Yuan and Hetvi J and Huan Zhang and Jaidev Shriram and Kruno Lehamn and Luca Soldaini and Maarten Sap and Marc Peter Deisenroth and Maria Leonor Pacheco and Maria Ryskina and Martin Mundt and Melvin Selim Atay and Milind Agarwal and Nyx McLean and Pan Xu and A Pranav and Raj Korpan and Ruchira Ray and Sarah Mathew and Sarthak Arora and ST John and Tanvi Anand and Vishakha Agrawal and William Agnew and Yanan Long and Zijie J. Wang and Zeerak Talat and Avijit Ghosh and Nathaniel Dennler and Michael Noseworthy and Sharvani Jha and Emi Baylor and Aditya Joshi and Natalia Y. Bilenko and Andrew McNamara and Raphael Gontijo-Lopes and Alex Markham and Evyn D{\v o}ng and Jackie Kay and Manu Saraswat and Nikhil Vytla and Luke Stark}, title = {Queer in AI: A Case Study in Community-Led Participatory AI}, year = {2023}, archivePrefix = {arXiv}, arxivId = {2303.16972}, eprint = {2303.16972}, booktitle = {ACM Conference on Fairness, Accountability, and Transparency (FAccT)}, } @inproceedings{pogodin:circe, author = {Roman Pogodin and Namrata Deka and Yazhe Li and Danica J. Sutherland and Victor Veitch and Arthur Gretton}, title = {Efficient Conditionally Invariant Representation Learning}, year = {2023}, archivePrefix = {arXiv}, arxivId = {2212.08645}, eprint = {2212.08645}, booktitle = {International Conference on Learning Representations (ICLR)}, url = {https://openreview.net/forum?id=dJruFeSRym1}, } @inproceedings{ren:finetuning, author = {Yi Ren and Shangmin Guo and Wonho Bae and Danica J. Sutherland}, title = {How to prepare your task head for finetuning}, year = {2023}, archivePrefix = {arXiv}, arxivId = {2302.05779}, eprint = {2302.05779}, booktitle = {International Conference on Learning Representations (ICLR)}, url = {https://openreview.net/forum?id=gVOXZproe-e}, } @article{zhou:optimistic-rates, author = {Lijia Zhou and Frederic Koehler and Danica J. Sutherland and Nathan Srebro}, title = {Optimistic Rates: A Unifying Theory for Interpolation Learning and Regularization in Linear Regression}, year = {2023}, archivePrefix = {arXiv}, arxivId = {2112.04470}, eprint = {2112.04470}, journal = {ACM/IMS Journal of Data Science}, } @inproceedings{deka:mmd-bfair, author = {Namrata Deka and Danica J. Sutherland}, title = {{MMD-B-Fair}: Learning Fair Representations with Statistical Testing}, year = {2023}, archivePrefix = {arXiv}, arxivId = {2211.07907}, eprint = {2211.07907}, booktitle = {Artificial Intelligence and Statistics (AISTATS)}, } @article{harder:dp-mepf, author = {Frederik Harder and Milad {Jalali Asadabadi} and Danica J. Sutherland and Mijung Park}, title = {Pre-trained Perceptual Features Improve Differentially Private Image Generation}, year = {2023}, archivePrefix = {arXiv}, arxivId = {2205.12900}, eprint = {2205.12900}, journal = {Transactions on Machine Learning Research}, url = {https://openreview.net/forum?id=R6W7zkMz0P}, } @inproceedings{zhou:moreau, author = {Lijia Zhou and Frederic Koehler and Pragya Sur and Danica J. Sutherland and Nathan Srebro}, title = {A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models}, year = {2022}, archivePrefix = {arXiv}, arxivId = {2210.12082}, eprint = {2210.12082}, booktitle = {Neural Information Processing Systems (NeurIPS)}, } @inproceedings{mohamadi:active-ntk, author = {Mohamad Amin Mohamadi and Wonho Bae and Danica J. Sutherland}, title = {Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels}, year = {2022}, archivePrefix = {arXiv}, arxivId = {2206.12569}, eprint = {2206.12569}, booktitle = {Neural Information Processing Systems (NeurIPS)}, } @inproceedings{shirzad:contrastive-graph-eval, author = {Hamed Shirzad and Kaveh Hassani and Danica J. Sutherland}, title = {Evaluating Graph Generative Models with Contrastively Learned Features}, year = {2022}, archivePrefix = {arXiv}, arxivId = {2206.06234}, eprint = {2206.06234}, booktitle = {Neural Information Processing Systems (NeurIPS)}, } @inproceedings{seo:contrastive-wsod, author = {Jinhwan Seo and Wonho Bae and Danica J. Sutherland and Jyunhug Noh and Daijin Kim}, title = {Object Discovery via Contrastive Learning for Weakly Supervised Object Detection}, year = {2022}, archivePrefix = {arXiv}, arxivId = {2208.07576}, eprint = {2208.07576}, booktitle = {European Conference on Computer Vision (ECCV)}, } @inproceedings{bae:prediction-filtering, author = {Wonho Bae and Jyunhug Noh and Milad {Jalali Asadabadi} and Danica J. Sutherland}, title = {One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model}, year = {2022}, archivePrefix = {arXiv}, arxivId = {2205.01233}, eprint = {2205.01233}, booktitle = {International Joint Conference on Artificial Intelligence (IJCAI)}, } @inproceedings{ren:learning-path, author = {Yi Ren and Shangmin Guo and Danica J. Sutherland}, title = {Better Supervisory Signals by Observing Learning Paths}, year = {2022}, archivePrefix = {arXiv}, arxivId = {2203.02485}, eprint = {2203.02485}, booktitle = {International Conference on Learning Representations (ICLR)}, url = {https://openreview.net/forum?id=Iog0djAdbHj}, } @inproceedings{deka:private-mmd, author = {Namrata Deka and Danica J. Sutherland}, title = {Learning Privacy-Preserving Deep Kernels with Known Demographics}, year = {2022}, booktitle = {Privacy-Preserving Artificial Intelligence (AAAI workshop)}, } @inproceedings{koehler:gaussian-interpolators, author = {Frederic Koehler and Lijia Zhou and Danica J. Sutherland and Nathan Srebro}, title = {Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds and Benign Overfitting}, year = {2021}, archivePrefix = {arXiv}, arxivId = {2106.09276}, eprint = {2106.09276}, booktitle = {Neural Information Processing Systems (NeurIPS)}, url = {https://proceedings.neurips.cc/paper/2021/hash/ac9815bef801f58de83804bce86984ad-Abstract.html}, } @inproceedings{li:ssl-hsic, author = {Yazhe Li and Roman Pogodin and Danica J. Sutherland and Arthur Gretton}, title = {Self-Supervised Learning with Kernel Dependence Maximization}, year = {2021}, archivePrefix = {arXiv}, arxivId = {2106.08320}, eprint = {2106.08320}, booktitle = {Neural Information Processing Systems (NeurIPS)}, url = {https://proceedings.neurips.cc/paper/2021/hash/83004190b1793d7aa15f8d0d49a13eba-Abstract.html}, } @inproceedings{liu:meta-2st, author = {Feng Liu and Wenkai Xu and Jie Lu and Danica J. Sutherland}, title = {Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data}, year = {2021}, archivePrefix = {arXiv}, arxivId = {2106.07636}, eprint = {2106.07636}, booktitle = {Neural Information Processing Systems (NeurIPS)}, url = {https://proceedings.neurips.cc/paper/2021/hash/2e6d9c6052e99fcdfa61d9b9da273ca2-Abstract.html}, } @inproceedings{queerinai:queerinai-dni, author = {Organizers of QueerInAI and A Pranav and MaryLena Bleile and Arjun Subramonian and Luca Soldaini and Danica J. Sutherland and Sabine Weber and Pan Xu}, title = {How to Make Virtual Conferences Queer-Friendly: A Guide}, year = {2021}, booktitle = {Workshop on Widening NLP (EMNLP workshop)}, } @article{flamary:pot, author = {R{\'e}mi Flamary and Nicolas Courty and Alexandre Gramfort and Mokhtar Z. Alaya and Aur{\'e}lie Boisbunon and Stanislas Chambon and Laetitia Chapel and Adrien Corenflos and Kilian Fatras and Nemo Fournier and L{\'e}o Gautheron and Nathalie T.H. Gayraud and Hicham Janati and Alain Rakotomamonjy and Ievgen Redko and Antoine Rolet and Antony Schutz and Vivien Seguy and Danica J. Sutherland and Romain Tavenard and Alexander Tong and Titouan Vayer}, title = {{POT}: {P}ython {O}ptimal {T}ransport}, year = {2021}, journal = {Journal of Machine Learning Research}, url = {https://jmlr.org/papers/v22/20-451.html}, } @inproceedings{kamath:irm, author = {Pritish Kamath and Akilesh Tangella and Danica J. Sutherland and Nathan Srebro}, title = {Does {I}nvariant {R}isk {M}inimization Capture Invariance?}, year = {2021}, archivePrefix = {arXiv}, arxivId = {2101.01134}, eprint = {2101.01134}, booktitle = {Artificial Intelligence and Statistics (AISTATS)}, url = {http://proceedings.mlr.press/v130/kamath21a.html}, } @inproceedings{zhou:uniform-interpolation, author = {Lijia Zhou and Danica J. Sutherland and Nathan Srebro}, title = {On Uniform Convergence and Low-Norm Interpolation Learning}, year = {2020}, archivePrefix = {arXiv}, arxivId = {2006.05942}, eprint = {2006.05942}, booktitle = {Neural Information Processing Systems (NeurIPS)}, url = {https://proceedings.neurips.cc/paper/2020/hash/4cc5400e63624c44fadeda99f57588a6-Abstract.html}, } @inproceedings{liu:deep-testing, author = {Feng Liu and Wenkai Xu and Jie Lu and Guangquan Zhang and Arthur Gretton and Danica J. Sutherland}, title = {Learning Deep Kernels for Non-Parametric Two-Sample Tests}, year = {2020}, archivePrefix = {arXiv}, arxivId = {2002.09116}, eprint = {2002.09116}, booktitle = {International Conference on Machine Learning (ICML)}, url = {http://proceedings.mlr.press/v119/liu20m.html}, } @inproceedings{wenliang:dkef, author = {Li Wenliang and Danica J. Sutherland and Heiko Strathmann and Arthur Gretton}, title = {Learning deep kernels for exponential family densities}, year = {2019}, archivePrefix = {arXiv}, arxivId = {1811.08357}, eprint = {1811.08357}, booktitle = {International Conference on Machine Learning (ICML)}, url = {http://proceedings.mlr.press/v97/wenliang19a.html}, } @misc{sutherland:unbiased-mmd-variance, author = {Danica J. Sutherland and Namrata Deka}, title = {Unbiased estimators for the variance of {MMD} estimators}, year = {2019}, archivePrefix = {arXiv}, arxivId = {1906.02104}, eprint = {1906.02104}, } @misc{ntampaka:cosmo-ml, author = {Michelle Ntampaka and Camille Avestruz and Steven Boada and Jo{\~a}o Caldeira and Jessi Cisewski-Kehe and Rosanne {Di Stefano} and Cora Dvorkin and August E. Evrard and Arya Farahi and Doug Finkbeiner and Shy Genel and Alyssa Goodman and Andy Goulding and Shirley Ho and Arthur Kosowsky and Paul {La Plante} and Fran{\c c}ois Lanusse and Michelle Lochner and Rachel Mandelbaum and Daisuke Nagai and Jeffrey A. Newman and Brian Nord and J. E. G. Peek and Austin Peel and Barnab{\'a}s P{\'o}czos and Markus Michael Rau and Aneta Siemiginowska and Danica J. Sutherland and Hy Trac and Benjamin Wandelt}, title = {The Role of Machine Learning in the Next Decade of Cosmology}, year = {2019}, archivePrefix = {arXiv}, arxivId = {1902.10159}, eprint = {1902.10159}, } @inproceedings{arbel:smmd, author = {Michael Arbel and Danica J. Sutherland and Miko{\l}aj Bi{\'n}kowski and Arthur Gretton}, title = {On gradient regularizers for {MMD} {GAN}s}, year = {2018}, archivePrefix = {arXiv}, arxivId = {1805.11565}, eprint = {1805.11565}, booktitle = {Neural Information Processing Systems (NeurIPS)}, url = {http://papers.nips.cc/paper/7904-on-gradient-regularizers-for-mmd-gans}, } @inproceedings{binkowski:mmd-gans, author = {Miko{\l}aj Bi{\'n}kowski and Danica J. Sutherland and Michael Arbel and Arthur Gretton}, title = {Demystifying {MMD} {GAN}s}, year = {2018}, archivePrefix = {arXiv}, arxivId = {1801.01401}, eprint = {1801.01401}, booktitle = {International Conference on Learning Representations (ICLR)}, url = {https://openreview.net/forum?id=r1lUOzWCW}, } @inproceedings{sutherland:kexpfam-nystroem, author = {Danica J. Sutherland and Heiko Strathmann and Michael Arbel and Arthur Gretton}, title = {Efficient and principled score estimation with Nystr{\"o}m kernel exponential families}, year = {2018}, archivePrefix = {arXiv}, arxivId = {1705.08360}, eprint = {1705.08360}, booktitle = {Artificial Intelligence and Statistics (AISTATS)}, url = {http://proceedings.mlr.press/v84/sutherland18a.html}, } @inproceedings{law:bdr, author = {Ho Chung Leon Law and Danica J. Sutherland and Dino Sejdinovic and Seth Flaxman}, title = {Bayesian Approaches to Distribution Regression}, year = {2018}, archivePrefix = {arXiv}, arxivId = {1705.04293}, eprint = {1705.04293}, booktitle = {Artificial Intelligence and Statistics (AISTATS)}, url = {http://proceedings.mlr.press/v84/law18a.html}, } @inproceedings{law:bdr-workshop, author = {Ho Chung Leon Law and Danica J. Sutherland and Dino Sejdinovic and Seth Flaxman}, title = {Bayesian Approaches to Distribution Regression}, year = {2017}, booktitle = {Learning on Distributions, Functions, Graphs and Groups (NeurIPS workshop)}, url = {https://sites.google.com/site/nips2017learningon/11_paper.pdf}, } @inproceedings{sutherland:opt-mmd, author = {Danica J. Sutherland and Hsiao-Yu Tung and Heiko Strathmann and Soumyajit De and Aaditya Ramdas and Alex Smola and Arthur Gretton}, title = {Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy}, year = {2017}, archivePrefix = {arXiv}, arxivId = {1611.04488}, eprint = {1611.04488}, booktitle = {International Conference on Learning Representations (ICLR)}, url = {http://openreview.net/forum?id=HJWHIKqgl}, } @misc{sutherland:caponnetto-fix, author = {Danica J. Sutherland}, title = {Fixing an error in {C}aponnetto and de {V}ito (2007)}, year = {2017}, archivePrefix = {arXiv}, arxivId = {1702.02982}, eprint = {1702.02982}, } @misc{flaxman:trump-clinton, author = {Seth Flaxman and Danica J. Sutherland and Yu-Xiang Wang and Yee Whye Teh}, title = {Understanding the 2016 {US} Presidential Election using ecological inference and distribution regression with census microdata}, year = {2016}, archivePrefix = {arXiv}, arxivId = {1611.03787}, eprint = {1611.03787}, } @article{ntampaka:astro-interlopers, author = {Michelle Ntampaka and Hy Trac and Danica J. Sutherland and Sebastian Fromenteau and Barnab{\'a}s P{\'o}czos and Jeff Schneider}, title = {Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Machine Learning}, year = {2016}, archivePrefix = {arXiv}, arxivId = {1509.05409}, eprint = {1509.05409}, doi = {10.3847/0004-637X/831/2/135}, journal = {The Astrophysical Journal}, volume = {831}, number = {2}, pages = {135}, } @inproceedings{jin:nss, author = {Jay Jin and Kyle Miller and Danica J. Sutherland and Simon Labov and Karl Nelson and Artur Dubrawski}, title = {List Mode Regression for Low Count Detection}, year = {2016}, booktitle = {IEEE Nuclear Science Symposium (IEEE NSS/MIC)}, } @phdthesis{sutherland:thesis, author = {Danica J. Sutherland}, title = {Scalable, Flexible, and Active Learning on Distributions}, year = {2016}, type = {Ph.D. thesis}, school = {Carnegie Mellon University}, department = {Computer Science Department}, } @inproceedings{sutherland:hdd, author = {Danica J. Sutherland and Junier B. Oliva and Barnab{\'a}s P{\'o}czos and Jeff Schneider}, title = {Linear-time Learning on Distributions with Approximate Kernel Embeddings}, year = {2016}, archivePrefix = {arXiv}, arxivId = {1509.07553}, eprint = {1509.07553}, booktitle = {AAAI Conference on Artificial Intelligence (AAAI)}, url = {https://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/12460}, } @inproceedings{sutherland:hdd-workshop, author = {Danica J. Sutherland and Junier B. Oliva and Barnab{\'a}s P{\'o}czos and Jeff Schneider}, title = {Linear-time Learning on Distributions with Approximate Kernel Embeddings}, year = {2015}, booktitle = {Feature Extraction: Modern Questions and Challenges (NeurIPS workshop)}, } @misc{oliva:deep-mean-maps, author = {Junier B. Oliva and Danica J. Sutherland and Barnab{\'a}s P{\'o}czos and Jeff Schneider}, title = {Deep Mean Maps}, year = {2015}, archivePrefix = {arXiv}, arxivId = {1511.04150}, eprint = {1511.04150}, } @inproceedings{sutherland:rff, author = {Danica J. Sutherland and Jeff Schneider}, title = {On the Error of Random {F}ourier Features}, year = {2015}, archivePrefix = {arXiv}, arxivId = {1506.02785}, eprint = {1506.02785}, booktitle = {Uncertainty in Artificial Intelligence (UAI)}, url = {http://auai.org/uai2015/proceedings/supp/168_supp.pdf}, } @inproceedings{ma:apps, author = {Yifei Ma and Danica J. Sutherland and Roman Garnett and Jeff Schneider}, title = {Active Pointillistic Pattern Search}, year = {2015}, booktitle = {Artificial Intelligence and Statistics (AISTATS)}, url = {http://jmlr.org/proceedings/papers/v38/ma15.html}, } @article{ntampaka:astro, author = {Michelle Ntampaka and Hy Trac and Danica J. Sutherland and Nicholas Battaglia and Barnab{\'a}s P{\'o}czos and Jeff Schneider}, title = {A Machine Learning Approach for Dynamical Mass Measurements of Galaxy Clusters}, year = {2015}, archivePrefix = {arXiv}, arxivId = {1410.0686}, eprint = {1410.0686}, doi = {10.1088/0004-637X/803/2/50}, journal = {The Astrophysical Journal}, volume = {803}, number = {2}, pages = {50}, } @inproceedings{ma:apps-workshop, author = {Yifei Ma and Danica J. Sutherland and Roman Garnett and Jeff Schneider}, title = {Active Pointillistic Pattern Search}, year = {2014}, booktitle = {Bayesian Optimization (NeurIPS workshop)}, } @inproceedings{sutherland:active-mf, author = {Danica J. Sutherland and Barnab{\'a}s P{\'o}czos and Jeff Schneider}, title = {Active learning and search on low-rank matrices}, year = {2013}, doi = {10.1145/2487575.2487627}, booktitle = {Knowledge Discovery and Data Mining (KDD)}, } @inproceedings{poczos:sdm-cvpr, author = {Barnab{\'a}s P{\'o}czos and Liang Xiong and Danica J. Sutherland and Jeff Schneider}, title = {Nonparametric kernel estimators for image classification}, year = {2012}, doi = {10.1109/CVPR.2012.6248028}, booktitle = {Computer Vision and Pattern Recognition (CVPR)}, } @misc{sutherland:sdm-arxiv, author = {Danica J. Sutherland and Liang Xiong and Barnab{\'a}s P{\'o}czos and Jeff Schneider}, title = {Kernels on Sample Sets via Nonparametric Divergence Estimates}, year = {2012}, archivePrefix = {arXiv}, arxivId = {1202.0302}, eprint = {1202.0302}, } @inproceedings{stromme:guts, author = {Andrew Stromme and Danica J. Sutherland and Alexander Burka and Benjamin Lipton and Nicholas Felt and Rebecca Roelofs and Daniel-Elia Feist-Alexandrov and Steve Dini and Allen Welkie}, title = {Managing User Requests with the {G}rand {U}nified {T}ask {S}ystem ({GUTS})}, year = {2012}, booktitle = {Large Installation System Administration (LISA)}, url = {https://www.usenix.org/conference/lisa12/technical-sessions/presentation/stromme}, } @misc{bodenhamer:smrf, author = {Matthew Bodenhamer and Thomas Palmer and Danica J. Sutherland and Andrew H. Fagg}, title = {Grounding Conceptual Knowledge with Spatio-Temporal Multi-Dimensional Relational Framework Trees}, year = {2012}, } @thesis{sutherland:ba-thesis, author = {Danica J. Sutherland}, title = {Integrating Human Knowledge into a Relational Learning System}, year = {2011}, type = {B.A. thesis}, school = {Swarthmore College}, department = {Computer Science Department}, }