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ORCIDChristopher Ré
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- affiliation: Stanford University, Department of Computer Science
- affiliation: University of Wisconsin-Madison, USA
- affiliation: University of Washington, Seattle, Washington, USA
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2020 – today
- 2022
[j67]Piero Molino, Christopher Ré:
Declarative machine learning systems. Commun. ACM 65(1): 42-49 (2022)- [c162]Simran Arora, Sen Wu, Enci Liu, Christopher Ré:
Metadata Shaping: A Simple Approach for Knowledge-Enhanced Language Models. ACL (Findings) 2022: 1733-1745 - [c161]Megan Leszczynski, Daniel Y. Fu, Mayee F. Chen, Christopher Ré:
TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval. ACL (Findings) 2022: 2147-2166 - [i127]Nimit Sharad Sohoni, Maziar Sanjabi, Nicolas Ballas, Aditya Grover, Shaoliang Nie, Hamed Firooz, Christopher Ré:
BARACK: Partially Supervised Group Robustness With Guarantees. CoRR abs/2201.00072 (2022) - [i126]Karan Goel, Albert Gu, Chris Donahue, Christopher Ré:
It's Raw! Audio Generation with State-Space Models. CoRR abs/2202.09729 (2022) - [i125]Michael Zhang, Nimit Sharad Sohoni, Hongyang R. Zhang, Chelsea Finn, Christopher Ré:
Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations. CoRR abs/2203.01517 (2022) - [i124]Arjun D. Desai, Andrew M. Schmidt, Elka B. Rubin, Christopher M. Sandino, Marianne S. Black, Valentina Mazzoli, Kathryn J. Stevens, Robert Boutin, Christopher Ré, Garry Gold, Brian A. Hargreaves, Akshay S. Chaudhari:
SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation. CoRR abs/2203.06823 (2022) - [i123]Simran Arora, Patrick S. H. Lewis, Angela Fan, Jacob Kahn, Christopher Ré:
Reasoning over Public and Private Data in Retrieval-Based Systems. CoRR abs/2203.11027 (2022) - [i122]Mayee F. Chen, Daniel Y. Fu, Dyah Adila, Michael Zhang, Frederic Sala, Kayvon Fatahalian, Christopher Ré:
Shoring Up the Foundations: Fusing Model Embeddings and Weak Supervision. CoRR abs/2203.13270 (2022) - [i121]Sabri Eyuboglu, Maya Varma, Khaled Saab, Jean-Benoit Delbrouck, Christopher Lee-Messer, Jared Dunnmon, James Zou, Christopher Ré:
Domino: Discovering Systematic Errors with Cross-Modal Embeddings. CoRR abs/2203.14960 (2022) - [i120]Tri Dao, Beidi Chen, Nimit Sharad Sohoni, Arjun D. Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao, Atri Rudra, Christopher Ré:
Monarch: Expressive Structured Matrices for Efficient and Accurate Training. CoRR abs/2204.00595 (2022) - [i119]Mayee F. Chen, Daniel Y. Fu, Avanika Narayan, Michael Zhang, Zhao Song, Kayvon Fatahalian, Christopher Ré:
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning. CoRR abs/2204.07596 (2022) - [i118]Megan Leszczynski, Daniel Y. Fu, Mayee F. Chen, Christopher Ré:
TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval. CoRR abs/2204.08173 (2022) - [i117]Avanika Narayan, Ines Chami, Laurel J. Orr, Christopher Ré:
Can Foundation Models Wrangle Your Data? CoRR abs/2205.09911 (2022) - 2021
- [j66]Tim Kraska, Umar Farooq Minhas, Thomas Neumann, Olga Papaemmanouil, Jignesh M. Patel, Christopher Ré, Michael Stonebraker:
ML-In-Databases: Assessment and Prognosis. IEEE Data Eng. Bull. 44(1): 3-10 (2021) - [j65]Rebecca Sawyer Lee, Jared A. Dunnmon, Ann He, Siyi Tang
, Christopher Ré, Daniel L. Rubin:
Comparison of segmentation-free and segmentation-dependent computer-aided diagnosis of breast masses on a public mammography dataset. J. Biomed. Informatics 113: 103656 (2021) - [j64]Sahaana Suri, Ihab F. Ilyas, Christopher Ré, Theodoros Rekatsinas:
Ember: No-Code Context Enrichment via Similarity-Based Keyless Joins. Proc. VLDB Endow. 15(3): 699-712 (2021) - [j63]Piero Molino, Christopher Ré:
Declarative Machine Learning Systems: The future of machine learning will depend on it being in the hands of the rest of us. ACM Queue 19(3): 46-76 (2021) - [c160]Mayee F. Chen, Benjamin Cohen-Wang, Stephen Mussmann, Frederic Sala, Christopher Ré:
Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation. AISTATS 2021: 3286-3294 - [c159]Laurel J. Orr, Megan Leszczynski, Neel Guha, Sen Wu, Simran Arora, Xiao Ling, Christopher Ré:
Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation. CIDR 2021 - [c158]Maya Varma, Laurel J. Orr, Sen Wu, Megan Leszczynski, Xiao Ling, Christopher Ré:
Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text. EMNLP (Findings) 2021: 4566-4575 - [c157]Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava, Christopher Ré:
MONGOOSE: A Learnable LSH Framework for Efficient Neural Network Training. ICLR 2021 - [c156]Karan Goel, Albert Gu, Yixuan Li, Christopher Ré:
Model Patching: Closing the Subgroup Performance Gap with Data Augmentation. ICLR 2021 - [c155]Sarah M. Hooper, Michael Wornow, Ying Hang Seah, Peter Kellman, Hui Xue, Frederic Sala, Curtis P. Langlotz, Christopher Ré:
Cut out the annotator, keep the cutout: better segmentation with weak supervision. ICLR 2021 - [c154]Ines Chami, Albert Gu, Dat Nguyen, Christopher Ré:
HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections. ICML 2021: 1419-1429 - [c153]Mayee F. Chen, Karan Goel, Nimit Sharad Sohoni, Fait Poms, Kayvon Fatahalian, Christopher Ré:
Mandoline: Model Evaluation under Distribution Shift. ICML 2021: 1617-1629 - [c152]Jared Quincy Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Ré, Chelsea Finn, Percy Liang:
Catformer: Designing Stable Transformers via Sensitivity Analysis. ICML 2021: 2489-2499 - [c151]Khaled Saab, Sarah M. Hooper, Nimit Sharad Sohoni, Jupinder Parmar, Brian Pogatchnik, Sen Wu, Jared A. Dunnmon, Hongyang R. Zhang, Daniel L. Rubin, Christopher Ré:
Observational Supervision for Medical Image Classification Using Gaze Data. MICCAI (2) 2021: 603-614 - [c150]Bowen Yang, Jian Zhang, Jonathan Li, Christopher Ré, Christopher R. Aberger, Christopher De Sa:
PipeMare: Asynchronous Pipeline Parallel DNN Training. MLSys 2021 - [c149]Karan Goel, Nazneen Fatema Rajani, Jesse Vig, Zachary Taschdjian, Mohit Bansal, Christopher Ré:
Robustness Gym: Unifying the NLP Evaluation Landscape. NAACL-HLT (Demonstrations) 2021: 42-55 - [c148]Karan Goel, Laurel J. Orr, Nazneen Fatema Rajani, Jesse Vig, Christopher Ré:
Goodwill Hunting: Analyzing and Repurposing Off-the-Shelf Named Entity Linking Systems. NAACL-HLT (Industry Papers) 2021: 205-213 - [c147]Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré:
Scatterbrain: Unifying Sparse and Low-rank Attention. NeurIPS 2021: 17413-17426 - [c146]Arjun D. Desai, Andrew M. Schmidt, Elka B. Rubin, Christopher M. Sandino, Marianne Black, Valentina Mazzoli, Kathryn J. Stevens, Robert Boutin, Christopher Ré, Garry Gold, Brian A. Hargreaves, Akshay Chaudhari:
SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation. NeurIPS Datasets and Benchmarks 2021 - [c145]Albert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, Christopher Ré:
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers. NeurIPS 2021: 572-585 - [c144]Avanika Narayan, Piero Molino, Karan Goel, Willie Neiswanger, Christopher Ré:
Personalized Benchmarking with the Ludwig Benchmarking Toolkit. NeurIPS Datasets and Benchmarks 2021 - [c143]Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar:
Rethinking Neural Operations for Diverse Tasks. NeurIPS 2021: 15855-15869 - [i116]Karan Goel, Nazneen Fatema Rajani, Jesse Vig, Samson Tan, Jason Wu, Stephan Zheng, Caiming Xiong, Mohit Bansal, Christopher Ré:
Robustness Gym: Unifying the NLP Evaluation Landscape. CoRR abs/2101.04840 (2021) - [i115]Mayee F. Chen, Benjamin Cohen-Wang, Stephen Mussmann, Frederic Sala, Christopher Ré:
Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation. CoRR abs/2103.02761 (2021) - [i114]Nicholas Roberts, Mikhail Khodak, Tri Dao, Liam Li, Christopher Ré, Ameet Talwalkar:
Rethinking Neural Operations for Diverse Tasks. CoRR abs/2103.15798 (2021) - [i113]Sahaana Suri, Ihab F. Ilyas, Christopher Ré, Theodoros Rekatsinas:
Ember: No-Code Context Enrichment via Similarity-Based Keyless Joins. CoRR abs/2106.01501 (2021) - [i112]Ines Chami, Albert Gu, Dat Nguyen, Christopher Ré:
HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections. CoRR abs/2106.03306 (2021) - [i111]Mayee F. Chen, Karan Goel, Nimit Sharad Sohoni, Fait Poms, Kayvon Fatahalian, Christopher Ré:
Mandoline: Model Evaluation under Distribution Shift. CoRR abs/2107.00643 (2021) - [i110]Piero Molino, Christopher Ré:
Declarative Machine Learning Systems. CoRR abs/2107.08148 (2021) - [i109]Armin W. Thomas, Christopher Ré, Russell A. Poldrack:
Challenges for cognitive decoding using deep learning methods. CoRR abs/2108.06896 (2021) - [i108]Arjun D. Desai, Batu M. Ozturkler, Christopher M. Sandino, Shreyas Vasanawala, Brian A. Hargreaves, Christopher Ré, John M. Pauly, Akshay S. Chaudhari:
Noise2Recon: A Semi-Supervised Framework for Joint MRI Reconstruction and Denoising. CoRR abs/2110.00075 (2021) - [i107]Maya Varma, Laurel J. Orr, Sen Wu, Megan Leszczynski, Xiao Ling, Christopher Ré:
Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text. CoRR abs/2110.08228 (2021) - [i106]Simran Arora, Sen Wu, Enci Liu, Christopher Ré:
Metadata Shaping: Natural Language Annotations for the Tail. CoRR abs/2110.08430 (2021) - [i105]Albert Gu, Isys Johnson, Karan Goel, Khaled Saab, Tri Dao, Atri Rudra, Christopher Ré:
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers. CoRR abs/2110.13985 (2021) - [i104]Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, Christopher Ré:
Scatterbrain: Unifying Sparse and Low-rank Attention Approximation. CoRR abs/2110.15343 (2021) - [i103]Albert Gu, Karan Goel, Christopher Ré:
Efficiently Modeling Long Sequences with Structured State Spaces. CoRR abs/2111.00396 (2021) - [i102]Avanika Narayan, Piero Molino, Karan Goel, Willie Neiswanger, Christopher Ré:
Personalized Benchmarking with the Ludwig Benchmarking Toolkit. CoRR abs/2111.04260 (2021) - [i101]Beidi Chen, Tri Dao, Kaizhao Liang, Jiaming Yang, Zhao Song, Atri Rudra, Christopher Ré:
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models. CoRR abs/2112.00029 (2021) - 2020
- [j62]Emily K. Mallory, Matthieu de Rochemonteix, Alexander Ratner, Ambika Acharya, Christopher Ré, Roselie A. Bright, Russ B. Altman:
Extracting chemical reactions from text using Snorkel. BMC Bioinform. 21(1): 217 (2020) - [j61]Kun-Hsing Yu, Feiran Wang, Gerald J. Berry, Christopher Ré, Russ B. Altman, Michael Snyder, Isaac S. Kohane:
Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks. J. Am. Medical Informatics Assoc. 27(5): 757-769 (2020) - [j60]Jared A. Dunnmon, Alexander J. Ratner, Khaled Saab, Nishith Khandwala, Matthew Markert, Hersh Sagreiya, Roger E. Goldman, Christopher Lee-Messer, Matthew P. Lungren, Daniel L. Rubin, Christopher Ré:
Cross-Modal Data Programming Enables Rapid Medical Machine Learning. Patterns 1(2): 100019 (2020) - [j59]Sahaana Suri, Abishek Sethi, Girija Narlikar, Neslihan Bulut, Raghuveer Chanda, Sugato Basu, Pradyumna Narayana, Peter Bailis, Christopher Ré, Yemao Zeng:
Leveraging Organizational Resources to Adapt Models to New Data Modalities. Proc. VLDB Endow. 13(12): 3396-3410 (2020) - [j58]Luke Hsiao, Sen Wu, Nicholas Chiang, Christopher Ré, Philip Alexander Levis:
Creating Hardware Component Knowledge Bases with Training Data Generation and Multi-task Learning. ACM Trans. Embed. Comput. Syst. 19(6): 42:1-42:26 (2020) - [j57]Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason A. Fries, Sen Wu, Christopher Ré:
Snorkel: rapid training data creation with weak supervision. VLDB J. 29(2-3): 709-730 (2020) - [c142]Simran Arora, Avner May, Jian Zhang, Christopher Ré:
Contextual Embeddings: When Are They Worth It? ACL 2020: 2650-2663 - [c141]Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi, Christopher Ré:
Low-Dimensional Hyperbolic Knowledge Graph Embeddings. ACL 2020: 6901-6914 - [c140]Zhaobin Kuang, Frederic Sala, Nimit Sharad Sohoni, Sen Wu, Aldo Córdova-Palomera, Jared Dunnmon, James Priest, Christopher Ré:
Ivy: Instrumental Variable Synthesis for Causal Inference. AISTATS 2020: 398-410 - [c139]Luke Oakden-Rayner, Jared Dunnmon, Gustavo Carneiro, Christopher Ré:
Hidden stratification causes clinically meaningful failures in machine learning for medical imaging. CHIL 2020: 151-159 - [c138]Christopher Ré:
Overton: A Data System for Monitoring and Improving Machine-Learned Products. CIDR 2020 - [c137]Anna C. Gilbert, Albert Gu, Christopher Ré, Atri Rudra, Mary Wootters:
Sparse Recovery for Orthogonal Polynomial Transforms. ICALP 2020: 58:1-58:16 - [c136]Sen Wu, Hongyang R. Zhang, Christopher Ré:
Understanding and Improving Information Transfer in Multi-Task Learning. ICLR 2020 - [c135]Tri Dao, Nimit Sharad Sohoni, Albert Gu, Matthew Eichhorn, Amit Blonder, Megan Leszczynski, Atri Rudra, Christopher Ré:
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps. ICLR 2020 - [c134]Daniel Y. Fu, Mayee F. Chen, Frederic Sala, Sarah M. Hooper, Kayvon Fatahalian, Christopher Ré:
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods. ICML 2020: 3280-3291 - [c133]Sen Wu, Hongyang R. Zhang, Gregory Valiant, Christopher Ré:
On the Generalization Effects of Linear Transformations in Data Augmentation. ICML 2020: 10410-10420 - [c132]Megan Leszczynski, Avner May, Jian Zhang, Sen Wu, Christopher R. Aberger, Christopher Ré:
Understanding the Downstream Instability of Word Embeddings. MLSys 2020 - [c131]Ines Chami, Albert Gu, Vaggos Chatziafratis, Christopher Ré:
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering. NeurIPS 2020 - [c130]Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, Christopher Ré:
HiPPO: Recurrent Memory with Optimal Polynomial Projections. NeurIPS 2020 - [c129]Nimit Sharad Sohoni, Jared Dunnmon, Geoffrey Angus, Albert Gu, Christopher Ré:
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems. NeurIPS 2020 - [i100]Daniel Y. Fu, Mayee F. Chen, Frederic Sala, Sarah M. Hooper, Kayvon Fatahalian, Christopher Ré:
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods. CoRR abs/2002.11955 (2020) - [i99]Megan Leszczynski, Avner May, Jian Zhang, Sen Wu, Christopher R. Aberger, Christopher Ré:
Understanding the Downstream Instability of Word Embeddings. CoRR abs/2003.04983 (2020) - [i98]Sarah M. Hooper, Jared A. Dunnmon, Matthew P. Lungren, Sanjiv Sam Gambhir, Christopher Ré, Adam S. Wang, Bhavik N. Patel:
Assessing Robustness to Noise: Low-Cost Head CT Triage. CoRR abs/2003.07977 (2020) - [i97]Zhaobin Kuang, Frederic Sala, Nimit Sharad Sohoni, Sen Wu, Aldo Córdova-Palomera, Jared Dunnmon, James Priest, Christopher Ré:
Ivy: Instrumental Variable Synthesis for Causal Inference. CoRR abs/2004.05316 (2020) - [i96]Ines Chami, Adva Wolf, Da-Cheng Juan, Frederic Sala, Sujith Ravi, Christopher Ré:
Low-Dimensional Hyperbolic Knowledge Graph Embeddings. CoRR abs/2005.00545 (2020) - [i95]Sen Wu, Hongyang R. Zhang, Gregory Valiant, Christopher Ré:
On the Generalization Effects of Linear Transformations in Data Augmentation. CoRR abs/2005.00695 (2020) - [i94]Sen Wu, Hongyang R. Zhang, Christopher Ré:
Understanding and Improving Information Transfer in Multi-Task Learning. CoRR abs/2005.00944 (2020) - [i93]Ines Chami, Sami Abu-El-Haija, Bryan Perozzi, Christopher Ré, Kevin Murphy:
Machine Learning on Graphs: A Model and Comprehensive Taxonomy. CoRR abs/2005.03675 (2020) - [i92]Simran Arora, Avner May, Jian Zhang, Christopher Ré:
Contextual Embeddings: When Are They Worth It? CoRR abs/2005.09117 (2020) - [i91]Mayee F. Chen, Daniel Y. Fu, Frederic Sala, Sen Wu, Ravi Teja Mullapudi, Fait Poms, Kayvon Fatahalian, Christopher Ré:
Train and You'll Miss It: Interactive Model Iteration with Weak Supervision and Pre-Trained Embeddings. CoRR abs/2006.15168 (2020) - [i90]Kevin Kiningham, Christopher Ré, Philip Alexander Levis:
GRIP: A Graph Neural Network Accelerator Architecture. CoRR abs/2007.13828 (2020) - [i89]Karan Goel, Albert Gu, Yixuan Li, Christopher Ré:
Model Patching: Closing the Subgroup Performance Gap with Data Augmentation. CoRR abs/2008.06775 (2020) - [i88]Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, Christopher Ré:
HiPPO: Recurrent Memory with Optimal Polynomial Projections. CoRR abs/2008.07669 (2020) - [i87]Sahaana Suri, Raghuveer Chanda, Neslihan Bulut, Pradyumna Narayana, Yemao Zeng, Peter Bailis, Sugato Basu, Girija Narlikar, Christopher Ré, Abishek Sethi:
Leveraging Organizational Resources to Adapt Models to New Data Modalities. CoRR abs/2008.09983 (2020) - [i86]Ines Chami, Albert Gu, Vaggos Chatziafratis, Christopher Ré:
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering. CoRR abs/2010.00402 (2020) - [i85]Laurel J. Orr, Megan Leszczynski, Simran Arora, Sen Wu, Neel Guha, Xiao Ling, Christopher Ré:
Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation. CoRR abs/2010.10363 (2020) - [i84]Hongyang R. Zhang, Fan Yang, Sen Wu, Weijie J. Su, Christopher Ré:
Sharp Bias-variance Tradeoffs of Hard Parameter Sharing in High-dimensional Linear Regression. CoRR abs/2010.11750 (2020) - [i83]Nimit Sharad Sohoni, Jared A. Dunnmon, Geoffrey Angus, Albert Gu, Christopher Ré:
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems. CoRR abs/2011.12945 (2020) - [i82]Tri Dao, Nimit Sharad Sohoni, Albert Gu, Matthew Eichhorn, Amit Blonder, Megan Leszczynski, Atri Rudra, Christopher Ré:
Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps. CoRR abs/2012.14966 (2020)
2010 – 2019
- 2019
- [j56]Daniel Abadi, Anastasia Ailamaki, David G. Andersen, Peter Bailis, Magdalena Balazinska, Philip A. Bernstein, Peter A. Boncz, Surajit Chaudhuri, Alvin Cheung, AnHai Doan, Luna Dong, Michael J. Franklin, Juliana Freire, Alon Y. Halevy, Joseph M. Hellerstein, Stratos Idreos, Donald Kossmann, Tim Kraska, Sailesh Krishnamurthy, Volker Markl, Sergey Melnik, Tova Milo, C. Mohan, Thomas Neumann, Beng Chin Ooi, Fatma Ozcan, Jignesh M. Patel, Andrew Pavlo, Raluca A. Popa, Raghu Ramakrishnan, Christopher Ré, Michael Stonebraker, Dan Suciu:
The Seattle Report on Database Research. SIGMOD Rec. 48(4): 44-53 (2019) - [j55]Cody Coleman, Daniel Kang, Deepak Narayanan, Luigi Nardi, Tian Zhao, Jian Zhang, Peter Bailis, Kunle Olukotun, Christopher Ré, Matei Zaharia:
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark. ACM SIGOPS Oper. Syst. Rev. 53(1): 14-25 (2019) - [c128]Alexander Ratner, Braden Hancock, Jared Dunnmon, Frederic Sala, Shreyash Pandey, Christopher Ré:
Training Complex Models with Multi-Task Weak Supervision. AAAI 2019: 4763-4771 - [c127]Jian Zhang, Avner May, Tri Dao, Christopher Ré:
Low-Precision Random Fourier Features for Memory-constrained Kernel Approximation. AISTATS 2019: 1264-1274 - [c126]Kun-Hsing Yu, Feiran Wang, Gerald J. Berry, Christopher Ré, Russ B. Altman, Michael Snyder, Isaac S. Kohane:
Classifying Non-Small Cell Lung Cancer Histopathology Types and Transcriptomic Subtypes using Convolutional Neural Networks. AMIA 2019 - [c125]Alexander J. Ratner, Braden Hancock, Christopher Ré:
The Role of Massively Multi-Task and Weak Supervision in Software 2.0. CIDR 2019 - [c124]Ranjay Krishna, Vincent S. Chen, Paroma Varma, Michael S. Bernstein, Christopher Ré, Li Fei-Fei:
Scene Graph Prediction With Limited Labels. ICCV 2019: 2580-2590 - [c123]Vincent S. Chen, Paroma Varma, Ranjay Krishna, Michael S. Bernstein, Christopher Ré, Li Fei-Fei:
Scene Graph Prediction with Limited Labels. ICCV Workshops 2019: 1772-1782 - [c122]Christopher De Sa, Ihab F. Ilyas, Benny Kimelfeld, Christopher Ré, Theodoros Rekatsinas:
A Formal Framework for Probabilistic Unclean Databases. ICDT 2019: 6:1-6:18 - [c121]Albert Gu, Frederic Sala, Beliz Gunel, Christopher Ré:
Learning Mixed-Curvature Representations in Product Spaces. ICLR (Poster) 2019 - [c120]Tri Dao, Albert Gu, Matthew Eichhorn, Atri Rudra, Christopher Ré:
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations. ICML 2019: 1517-1527 - [c119]Tri Dao, Albert Gu, Alexander Ratner, Virginia Smith, Chris De Sa, Christopher Ré:
A Kernel Theory of Modern Data Augmentation. ICML 2019: 1528-1537 - [c118]Paroma Varma, Frederic Sala, Ann He, Alexander Ratner, Christopher Ré:
Learning Dependency Structures for Weak Supervision Models. ICML 2019: 6418-6427 - [c117]Zhenzhen Weng, Paroma Varma, Alexander Masalov, Jeffrey M. Ota, Christopher Ré:
Utilizing Weak Supervision to Infer Complex Objects and Situations in Autonomous Driving Data. IV 2019: 119-125 - [c116]Luke Hsiao, Sen Wu, Nicholas Chiang, Christopher Ré, Philip Alexander Levis:
Automating the generation of hardware component knowledge bases. LCTES 2019: 163-176 - [c115]Khaled Saab, Jared Dunnmon, Roger E. Goldman, Alexander Ratner, Hersh Sagreiya, Christopher Ré, Daniel L. Rubin:
Doubly Weak Supervision of Deep Learning Models for Head CT. MICCAI (3) 2019: 811-819 - [c114]Paroma Varma, Frederic Sala, Shiori Sagawa, Jason Alan Fries, Daniel Y. Fu, Saelig Khattar, Ashwini Ramamoorthy, Ke Xiao, Kayvon Fatahalian, James Priest, Christopher Ré:
Multi-Resolution Weak Supervision for Sequential Data. NeurIPS 2019: 192-203 - [c113]Ines Chami, Zhitao Ying, Christopher Ré, Jure Leskovec:
Hyperbolic Graph Convolutional Neural Networks. NeurIPS 2019: 4869-4880 - [c112]Vincent S. Chen, Sen Wu, Alexander J. Ratner, Jen Weng, Christopher Ré:
Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices. NeurIPS 2019: 9392-9402 - [c111]Avner May, Jian Zhang, Tri Dao, Christopher Ré:
On the Downstream Performance of Compressed Word Embeddings. NeurIPS 2019: 11782-11793 - [c110]Eran Bringer, Abraham Israeli, Yoav Shoham, Alexander Ratner, Christopher Ré:
Osprey: Weak Supervision of Imbalanced Extraction Problems without Code. DEEM@SIGMOD 2019: 4:1-4:11 - [c109]Stephen H. Bach, Daniel Rodriguez, Yintao Liu, Chong Luo, Haidong Shao, Cassandra Xia, Souvik Sen, Alexander Ratner, Braden Hancock, Houman Alborzi, Rahul Kuchhal, Christopher Ré, Rob Malkin:
Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale. SIGMOD Conference 2019: 362-375 - [i81]Paroma Varma, Frederic Sala, Ann He, Alexander Ratner, Christopher Ré:
Learning Dependency Structures for Weak Supervision Models. CoRR abs/1903.05844 (2019) - [i80]Tri Dao, Albert Gu, Matthew Eichhorn, Atri Rudra, Christopher Ré:
Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations. CoRR abs/1903.05895 (2019) - [i79]Jared Dunnmon, Alexander Ratner, Nishith Khandwala, Khaled Saab, Matthew Markert, Hersh Sagreiya, Roger E. Goldman, Christopher Lee-Messer, Matthew P. Lungren, Daniel L. Rubin, Christopher Ré:
Cross-Modal Data Programming Enables Rapid Medical Machine Learning. CoRR abs/1903.11101 (2019) - [i78]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf,