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ORCIDNathan Ng
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2020 – today
- 2024
[j5]Nathan H. Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho:
Blind Biological Sequence Denoising with Self-Supervised Set Learning. Trans. Mach. Learn. Res. 2024 (2024)- [c13]Nathan Ng
, Abel Souza, Ahmed Ali-Eldin, David E. Irwin, Don Towsley, Prashant J. Shenoy:
TailClipper: Reducing Tail Response Time of Distributed Services Through System-Wide Scheduling. SoCC 2024: 398-414 - [c12]Nathan H. Ng, Roger Baker Grosse, Marzyeh Ghassemi:
Measuring Stochastic Data Complexity with Boltzmann Influence Functions. ICML 2024 - [c11]Nathan Ng, Abel Souza, Suhas N. Diggavi, Niranjan Suri, Tarek F. Abdelzaher, Don Towsley, Prashant J. Shenoy:
Collaborative Inference in Resource-Constrained Edge Networks: Challenges and Opportunities. MILCOM 2024: 1-6 - [i13]Kyle O'Brien, Nathan Ng, Isha Puri, Jorge Mendez, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi, Thomas Hartvigsen:
Improving Black-box Robustness with In-Context Rewriting. CoRR abs/2402.08225 (2024) - [i12]Nathan Ng, Roger B. Grosse, Marzyeh Ghassemi:
Measuring Stochastic Data Complexity with Boltzmann Influence Functions. CoRR abs/2406.02745 (2024) - 2023
- [j4]Nathan H. Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi:
Predicting Out-of-Domain Generalization with Neighborhood Invariance. Trans. Mach. Learn. Res. 2023 (2023) - [c10]Abel Souza, Nathan Ng, Tarek F. Abdelzaher, Don Towsley, Prashant J. Shenoy:
Unlocking Efficiency: Understanding End-to-End Performance in Distributed Analytics Pipelines. MILCOM 2023: 150-155 - [i11]Nathan Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho:
Blind Biological Sequence Denoising with Self-Supervised Set Learning. CoRR abs/2309.01670 (2023) - 2022
- [c9]Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B. Grosse:
If Influence Functions are the Answer, Then What is the Question? NeurIPS 2022 - [i10]Nathan Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi:
Predicting Out-of-Domain Generalization with Local Manifold Smoothness. CoRR abs/2207.02093 (2022) - [i9]Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B. Grosse:
If Influence Functions are the Answer, Then What is the Question? CoRR abs/2209.05364 (2022) - [i8]Nathan Ng, Hung Le, Marco Serafini:
Tuning the Tail Latency of Distributed Queries Using Replication. CoRR abs/2212.10387 (2022) - 2021
- [j3]Samuel Broadbent, Habiba Kadiri, Allysa Lumley, Nathan Ng, Kirsten Wilk:
Sharper bounds for the Chebyshev function θ (x). Math. Comput. 90(331): 2281-2315 (2021) - [j2]Stephen R. Knight, Nathan Ng, Athanasios Tsanas, Kenneth A. McLean, Claudia Pagliari, Ewen M. Harrison:
Mobile devices and wearable technology for measuring patient outcomes after surgery: a systematic review. npj Digit. Medicine 4 (2021) - [j1]Muhamed Wael Farouq, Wadii Boulila, Zain U. Hussain, Asrar Rashid, Moiz Ali Shah, Sajid Hussain, Nathan Ng, Dominic Ng, Haris Hanif, M. Guftar Shaikh, Aziz Sheikh, Amir Hussain:
A Novel Coupled Reaction-Diffusion System for Explainable Gene Expression Profiling. Sensors 21(6): 2190 (2021) - 2020
- [c8]Nathan Ng, Kyunghyun Cho, Marzyeh Ghassemi:
SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness. EMNLP (1) 2020: 1268-1283 - [i7]Nathan Ng, Kyunghyun Cho, Marzyeh Ghassemi:
SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness. CoRR abs/2009.10195 (2020) - [i6]Nathan Ng, Marzyeh Ghassemi, Narendran Thangarajan, Jiacheng Pan, Qi Guo:
Improving Dialogue Breakdown Detection with Semi-Supervised Learning. CoRR abs/2011.00136 (2020)
2010 – 2019
- 2019
- [c7]Nathan Ng, Peipei Yi, Zhiwei Zhang, Byron Choi, Sourav S. Bhowmick, Jianliang Xu:
FGreat: Focused Graph Query Autocompletion. ICDE 2019: 1956-1959 - [c6]Tingfung Lau, Nathan Ng, Julian Gingold, Nina Desai, Julian J. McAuley, Zachary C. Lipton:
Embryo Staging with Weakly-Supervised Region Selection and Dynamically-Decoded Predictions. MLHC 2019: 663-679 - [c5]Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, Michael Auli:
fairseq: A Fast, Extensible Toolkit for Sequence Modeling. NAACL-HLT (Demonstrations) 2019: 48-53 - [c4]Nathan Ng, Kyra Yee, Alexei Baevski, Myle Ott, Michael Auli, Sergey Edunov:
Facebook FAIR's WMT19 News Translation Task Submission. WMT (2) 2019: 314-319 - [i5]Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, Michael Auli:
fairseq: A Fast, Extensible Toolkit for Sequence Modeling. CoRR abs/1904.01038 (2019) - [i4]Tingfung Lau, Nathan Ng, Julian Gingold, Nina Desai, Julian J. McAuley, Zachary C. Lipton:
Embryo staging with weakly-supervised region selection and dynamically-decoded predictions. CoRR abs/1904.04419 (2019) - [i3]Nathan Ng, Kyra Yee, Alexei Baevski, Myle Ott, Michael Auli, Sergey Edunov:
Facebook FAIR's WMT19 News Translation Task Submission. CoRR abs/1907.06616 (2019) - [i2]Kyra Yee, Nathan Ng, Yann N. Dauphin, Michael Auli:
Simple and Effective Noisy Channel Modeling for Neural Machine Translation. CoRR abs/1908.05731 (2019) - 2018
- [c3]Guozhong Li, Nathan Ng, Peipei Yi, Zhiwei Zhang, Byron Choi:
Answering the Why-Not Questions of Graph Query Autocompletion. DASFAA (1) 2018: 332-341 - [c2]Nathan H. Ng, Julian J. McAuley, Julian Gingold, Nina Desai, Zachary C. Lipton:
Predicting Embryo Morphokinetics in Videos with Late Fusion Nets & Dynamic Decoders. ICLR (Workshop) 2018 - 2017
- [c1]Nathan H. Ng, Rodney A. Gabriel, Julian J. McAuley, Charles Elkan, Zachary C. Lipton:
Predicting Surgery Duration with Neural Heteroscedastic Regression. MLHC 2017: 100-111 - [i1]Nathan Ng, Rodney A. Gabriel, Julian J. McAuley, Charles Elkan, Zachary C. Lipton:
Predicting Surgery Duration with Neural Heteroscedastic Regression. CoRR abs/1702.05386 (2017)
Coauthor Index
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