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ORCIDShashank Singh 0005
Person information
- affiliation: Carnegie Mellon University, Machine Learning Department, Pittsburgh, PA, USA
Other persons with the same name
- Shashank Singh 0001
![[0000-0002-4374-3125]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-4374-3125")
— Indian Institute of Science Education and Research Bhopal, India (and 1 more) - Shashank Singh 0002 — ABV - Indian Institute of Information Technology and Management, Gwalior, MP
- Shashank Singh 0003 — The Ohio State University
- Shashank Singh 0004 — Uttar Pradesh Technical University, Lucknow, India
- Shashank Singh 0006 — Samsung Electronics, Hwaseong, South Korea (and 4 more)
- Shashank Singh 0007 — National Institute of Technology, Tiruchirappalli, India
- Shashank Singh 0008 — Facebook, Menlo Park, CA, USA
- Shashank Singh 0009 — Punjab Engineering College (Deemed to be University), Chandigarh, India
- Shashank Singh 0010 — Manipal University Jaipur, Department of Computer and Communication Engineering, India
- Shashank Singh 0011 — Max Planck Institute for Intelligent Systems, Tübingen, Germany
- Shashank Singh 0012 — VIT Bhopal University, School of Computer Science and Engineering, India
- Shashank Singh 0013 — National Institute of Technology Raipur, Department of Computer Science and Engineering, India
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2020 – today
- 2022
[c18]Jaeah Kim, Shashank Singh, Dan Yurovsky, Anna V. Fisher, Erik D. Thiessen:
A Hierarchical Model of Attention over Time. CogSci 2022- [c17]Karan Uppal, Jaeah Kim, Shashank Singh:
Decoding Attention from Gaze: A Benchmark Dataset and End-to-End Models. Gaze Meets ML 2022: 219-240 - [c16]Shashank Singh, Justin T. Khim:
Optimal Binary Classification Beyond Accuracy. NeurIPS 2022 - [i18]Karan Uppal, Jaeah Kim, Shashank Singh:
Decoding Attention from Gaze: A Benchmark Dataset and End-to-End Models. CoRR abs/2211.10966 (2022) - 2021
- [j4]Sercan Ö. Arik, Joel Shor, Rajarishi Sinha, Jinsung Yoon, Joseph R. Ledsam, Long T. Le, Michael W. Dusenberry, Nathanael C. Yoder, Kris Popendorf, Arkady Epshteyn, Johan Euphrosine, Elli Kanal, Isaac Jones, Chun-Liang Li, Beth Luan, Joe Mckenna, Vikas Menon, Shashank Singh, Mimi Sun, Ashwin Sura Ravi, Leyou Zhang, Dario Sava, Kane Cunningham, Hiroki Kayama, Thomas C. Tsai, Daisuke Yoneoka, Shuhei Nomura, Hiroaki Miyata, Tomas Pfister:
A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan. npj Digit. Medicine 4 (2021) - [c15]Shashank Singh:
Continuum-Armed Bandits: A Function Space Perspective. AISTATS 2021: 2620-2628 - [i17]Shashank Singh, Justin Khim:
Statistical Theory for Imbalanced Binary Classification. CoRR abs/2107.01777 (2021) - 2020
- [b1]Shashank Singh:
Estimating Probability Distributions and their Properties. Carnegie Mellon University, USA, 2020 - [c14]Jaeah Kim, Shashank Singh, Erik D. Thiessen, Anna V. Fisher:
Staying and Returning Dynamics of Sustained Attention in Young Children. CogSci 2020 - [c13]Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister:
Interpretable Sequence Learning for Covid-19 Forecasting. NeurIPS 2020 - [c12]Ananya Uppal, Shashank Singh, Barnabás Póczos:
Robust Density Estimation under Besov IPM Losses. NeurIPS 2020 - [i16]Justin Khim, Ziyu Xu, Shashank Singh:
Multiclass Classification via Class-Weighted Nearest Neighbors. CoRR abs/2004.04715 (2020) - [i15]Ananya Uppal, Shashank Singh, Barnabás Póczos:
Robust Density Estimation under Besov IPM Losses. CoRR abs/2004.08597 (2020) - [i14]Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister:
Interpretable Sequence Learning for COVID-19 Forecasting. CoRR abs/2008.00646 (2020) - [i13]Shashank Singh:
Continuum-Armed Bandits: A Function Space Perspective. CoRR abs/2010.08007 (2020)
2010 – 2019
- 2019
- [j3]Shashank Singh, Yang Yang, Barnabás Póczos, Jian Ma:
Predicting enhancer-promoter interaction from genomic sequence with deep neural networks. Quant. Biol. 7(2): 122-137 (2019) - [j2]Sabrina Rashid, Shashank Singh, Saket Navlakha, Ziv Bar-Joseph:
A bacterial based distributed gradient descent model for mass scale evacuations. Swarm Evol. Comput. 46: 97-103 (2019) - [c11]Jaeah Kim, Shashank Singh, Emily Keebler, Erik D. Thiessen, Anna V. Fisher:
Measuring Selective Sustained Attention in Children with TrackIt and Eyetracking. CogSci 2019: 3296 - [c10]Ananya Uppal, Shashank Singh, Barnabás Póczos:
Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses. NeurIPS 2019: 9086-9097 - [i12]Ananya Uppal, Shashank Singh, Barnabás Póczos:
Nonparametric Density Estimation under Besov IPM Losses. CoRR abs/1902.03511 (2019) - [i11]Shashank Singh, Ashish Khetan, Zohar S. Karnin:
DARC: Differentiable ARchitecture Compression. CoRR abs/1905.08170 (2019) - 2018
- [c9]Shashank Singh, Barnabás Póczos, Jian Ma:
Minimax Reconstruction Risk of Convolutional Sparse Dictionary Learning. AISTATS 2018: 1327-1336 - [c8]Jaeah Kim, Shashank Singh, Anna Vande Velde, Erik D. Thiessen, Anna V. Fisher:
A Hidden Markov Model for Analyzing Eye-Tracking of Moving Objects. CogSci 2018 - [c7]Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, Barnabás Póczos:
Nonparametric Density Estimation under Adversarial Losses. NeurIPS 2018: 10246-10257 - [i10]Shashank Singh, Barnabás Póczos:
Minimax Distribution Estimation in Wasserstein Distance. CoRR abs/1802.08855 (2018) - [i9]Shashank Singh, Bharath K. Sriperumbudur, Barnabás Póczos:
Minimax Estimation of Quadratic Fourier Functionals. CoRR abs/1803.11451 (2018) - [i8]Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, Barnabás Póczos:
Nonparametric Density Estimation under Adversarial Losses. CoRR abs/1805.08836 (2018) - 2017
- [j1]Yang Yang, Ruochi Zhang, Shashank Singh, Jian Ma:
Exploiting sequence-based features for predicting enhancer-promoter interactions. Bioinform. 33(14): i252-i260 (2017) - [c6]Shashank Singh, Barnabás Póczos:
Nonparanormal Information Estimation. ICML 2017: 3210-3219 - [i7]Shashank Singh, Barnabás Póczos:
Nonparanormal Information Estimation. CoRR abs/1702.07803 (2017) - [i6]Shashank Singh, Barnabás Póczos, Jian Ma:
On the Reconstruction Risk of Convolutional Sparse Dictionary Learning. CoRR abs/1708.08587 (2017) - 2016
- [c5]Shashank Singh, Simon S. Du, Barnabás Póczos:
Efficient Nonparametric Smoothness Estimation. NIPS 2016: 1010-1018 - [c4]Shashank Singh, Barnabás Póczos:
Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators. NIPS 2016: 1217-1225 - [c3]Shashank Singh, Sabrina Rashid, Saket Navlakha, Ziv Bar-Joseph:
Distributed Gradient Descent in Bacterial Food Search. RECOMB 2016: 259-260 - [i5]Shashank Singh, Barnabás Póczos:
Analysis of k-Nearest Neighbor Distances with Application to Entropy Estimation. CoRR abs/1603.08578 (2016) - [i4]Shashank Singh, Barnabás Póczos:
Exponential Concentration of a Density Functional Estimator. CoRR abs/1603.08584 (2016) - [i3]Shashank Singh, Barnabás Póczos:
Generalized Exponential Concentration Inequality for Rényi Divergence Estimation. CoRR abs/1603.08589 (2016) - [i2]Shashank Singh, Simon S. Du, Barnabás Póczos:
Efficient Nonparametric Smoothness Estimation. CoRR abs/1605.05785 (2016) - [i1]Shashank Singh, Barnabás Póczos:
Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators. CoRR abs/1606.01554 (2016) - 2014
- [c2]Shashank Singh, Barnabás Póczos:
Generalized Exponential Concentration Inequality for Renyi Divergence Estimation. ICML 2014: 333-341 - [c1]Shashank Singh, Barnabás Póczos:
Exponential Concentration of a Density Functional Estimator. NIPS 2014: 3032-3040
Coauthor Index
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last updated on 2024-10-07 22:16 CEST by the dblp team
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