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Shashank Singh 0005
Person information
- affiliation: Carnegie Mellon University, Machine Learning Department, Pittsburgh, PA, USA
Other persons with the same name
- Shashank Singh 0001
— 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 2024-08-05 20:22 CEST by the dblp team
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