Mohak Shah

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 38

Top Topics

Multiclass Learning

Top Venues

Publications

Ankur Teredesai, Michael Zeller, Mohak Shah, Shenghua Bao, Wee Hyong Tok, Linsey Pang
The 2nd International Workshop: From Innovation to Scale (I2S) - Successfully Build, Commercialize, and Scale AI Innovations. KDD (2024)
Shengdong Zhang, Ehsan Nezhadarya, Homa Fashandi, Jiayi Liu, Darin Graham, Mohak Shah
Stochastic Whitening Batch Normalization. CoRR (2021)
Olimpiya Saha, Guohua Ren, Javad Heydari, Viswanath Ganapathy, Mohak Shah
Online Area Covering Robot in Unknown Dynamic Environments. ICARA (2021)
Sauptik Dhar, Javad Heydari, Samarth Tripathi, Unmesh Kurup, Mohak Shah
Evolving GANs: When Contradictions Turn into Compliance. CoRR (2021)
Olimpiya Saha, Viswanath Ganapathy, Javad Heydari, Guohua Ren, Mohak Shah
Efficient Coverage Path Planning in Initially Unknown Environments Using Graph Representation. ICAR (2021)
Olimpiya Saha, Guohua Ren, Javad Heydari, Viswanath Ganapathy, Mohak Shah
Deep Reinforcement Learning Based Online Area Covering Autonomous Robot. ICARA (2021)
Viswanath Ganapathy, Sauptik Dhar, Olimpiya Saha, Pelin Kurt Garberson, Javad Heydari, Mohak Shah
A Survey on Proactive Customer Care: Enabling Science and Steps to Realize it. CoRR (2021)
Sauptik Dhar, Junyao Guo, Jiayi (Jason) Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah
A Survey of On-Device Machine Learning: An Algorithms and Learning Theory Perspective. ACM Trans. Internet Things 2 (3) (2021)
Shengdong Zhang, Ehsan Nezhadarya, Homa Fashandi, Jiayi Liu, Darin Graham, Mohak Shah
Stochastic Whitening Batch Normalization. CVPR (2021)
Dimple Kaul, Mohak Shah, Neeraj Dhakephalkar
A Study on the Factors Influencing Behavioral Intention of Indian Consumers in Adopting Voice Assistants. TDIT (1) (2020)
Samarth Tripathi, Jiayi Liu, Sauptik Dhar, Unmesh Kurup, Mohak Shah
Improving Model Training by Periodic Sampling over Weight Distributions. IEEE BigData (2020)
Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah
Pruning Algorithms to Accelerate Convolutional Neural Networks for Edge Applications: A Survey. CoRR (2020)
Youngsuk Park, Sauptik Dhar, Stephen P. Boyd, Mohak Shah
Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize. ICASSP (2020)
Sauptik Dhar, Unmesh Kurup, Mohak Shah
Stabilizing Bi-Level Hyperparameter Optimization using Moreau-Yosida Regularization. CoRR (2020)
Junyao Guo, Unmesh Kurup, Mohak Shah
Is it Safe to Drive? An Overview of Factors, Metrics, and Datasets for Driveability Assessment in Autonomous Driving. IEEE Trans. Intell. Transp. Syst. 21 (8) (2020)
Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah
Auptimizer - an Extensible, Open-Source Framework for Hyperparameter Tuning. IEEE BigData (2019)
Sauptik Dhar, Junyao Guo, Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah
On-Device Machine Learning: An Algorithms and Learning Theory Perspective. CoRR (2019)
Shujian Yu, Zubin Abraham, Heng Wang, Mohak Shah, Yantao Wei, José C. Príncipe
Concept drift detection and adaptation with hierarchical hypothesis testing. J. Frankl. Inst. 356 (5) (2019)
Abdeltawab M. Hendawi, Jayant Gupta, Jiayi Liu, Ankur Teredesai, Naveen Ramakrishnan, Mohak Shah, Shaker H. Ali El-Sappagh, Kyung-Sup Kwak, Mohamed H. Ali
Benchmarking large-scale data management for Internet of Things. J. Supercomput. 75 (12) (2019)
Samarth Tripathi, Jiayi Liu, Unmesh Kurup, Mohak Shah
Robust Neural Network Training using Periodic Sampling over Model Weights. CoRR (2019)
Rayid Ghani, Lisa Green, Alberto Bengoa, Mohak Shah
Solve for Good: A Data Science for Social Good Marketplace. SIGKDD Explor. 21 (2) (2019)
Sauptik Dhar, Vladimir Cherkassky, Mohak Shah
Multiclass Learning from Contradictions. NeurIPS (2019)
Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah
Auptimizer - an Extensible, Open-Source Framework for Hyperparameter Tuning. CoRR (2019)
Javad Heydari, Viswanath Ganapathy, Mohak Shah
Dynamic Task Offloading in Multi-Agent Mobile Edge Computing Networks. GLOBECOM (2019)
Youngsuk Park, Sauptik Dhar, Stephen P. Boyd, Mohak Shah
Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize. CoRR (2019)
Junyao Guo, Unmesh Kurup, Mohak Shah
Is it Safe to Drive? An Overview of Factors, Challenges, and Datasets for Driveability Assessment in Autonomous Driving. CoRR (2018)
Sauptik Dhar, Vladimir Cherkassky, Mohak Shah
Multiclass Universum SVM. CoRR (2018)
Jiayi Liu, Samarth Tripathi, Unmesh Kurup, Mohak Shah
Make (Nearly) Every Neural Network Better: Generating Neural Network Ensembles by Weight Parameter Resampling. CoRR (2018)
Abdeltawab M. Hendawi, Jayant Gupta, Jiayi Liu, Ankur Teredesai, Naveen Ramakrishnan, Mohak Shah, Mohamed H. Ali
Distributed NoSQL Data Stores: Performance Analysis and a Case Study. IEEE BigData (2018)
Jayanta K. Dutta, Jiayi Liu, Unmesh Kurup, Mohak Shah
Effective Building Block Design for Deep Convolutional Neural Networks using Search. CoRR (2018)
Shengdong Zhang, Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah
Deep learning on symbolic representations for large-scale heterogeneous time-series event prediction. ICASSP (2017)
Pranjul Yadav, Unmesh Kurup, Mohak Shah
Structured Causal Inference for Rare Events: An Industrial Application to Analyze Heating-Cooling Device Failure. ICMLA (2017)
Shujian Yu, Zubin Abraham, Heng Wang, Mohak Shah, José C. Príncipe
Concept Drift Detection and Adaptation with Hierarchical Hypothesis Testing. CoRR (2017)
Seyed Hamid Mirebrahim, Mohammad Shokoohi-Yekta, Unmesh Kurup, Torsten Welfonder, Mohak Shah
A clustering-based rule-mining approach for monitoring long-term energy use and understanding system behavior. BuildSys@SenSys (2017)
Juergen Heit, Jiayi Liu, Mohak Shah
An architecture for the deployment of statistical models for the big data era. IEEE BigData (2016)
Shengdong Zhang, Soheil Bahrampour, Naveen Ramakrishnan, Mohak Shah
Deep Symbolic Representation Learning for Heterogeneous Time-series Classification. CoRR (2016)
Sauptik Dhar, Naveen Ramakrishnan, Vladimir Cherkassky, Mohak Shah
Universum Learning for Multiclass SVM. CoRR (2016)
Mark Grechanik, Nitin Prabhu, Daniel Graham, Denys Poshyvanyk, Mohak Shah
Can Software Project Maturity Be Accurately Predicted Using Internal Source Code Metrics? MLDM (2016)
Sauptik Dhar, Congrui Yi, Naveen Ramakrishnan, Mohak Shah
ADMM based scalable machine learning on Spark. IEEE BigData (2015)
Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah
Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning. CoRR (2015)
Mohak Shah
Big Data and the Internet of Things. CoRR (2015)
Zahra Karimaghaloo, Mohak Shah, Simon J. Francis, Douglas L. Arnold, D. Louis Collins, Tal Arbel
Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI Using Conditional Random Fields. IEEE Trans. Medical Imaging 31 (6) (2012)
Mohak Shah, Mario Marchand, Jacques Corbeil
Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data. IEEE Trans. Pattern Anal. Mach. Intell. 34 (1) (2012)
Heidar Pirzadeh, Abdelwahab Hamou-Lhadj, Mohak Shah
Exploiting text mining techniques in the analysis of execution traces. ICSM (2011)
Mohak Shah, Yiming Xiao, Nagesh K. Subbanna, Simon J. Francis, Douglas L. Arnold, D. Louis Collins, Tal Arbel
Evaluating intensity normalization on MRIs of human brain with multiple sclerosis. Medical Image Anal. 15 (2) (2011)
Mohak Shah
Generalized Agreement Statistics over Fixed Group of Experts. ECML/PKDD (3) (2011)
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la Torre, Frank P. Ferrie
Relaxed Exponential Kernels for Unsupervised Learning. DAGM-Symposium (2011)
Mohak Shah, Jacques Corbeil
A General Framework for Analyzing Data from Two Short Time-Series Microarray Experiments. IEEE ACM Trans. Comput. Biol. Bioinform. 8 (1) (2011)
François Laviolette, Mario Marchand, Mohak Shah, Sara Shanian
Learning the set covering machine by bound minimization and margin-sparsity trade-off. Mach. Learn. 78 (1-2) (2010)
Mohak Shah, Mario Marchand, Jacques Corbeil
Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data CoRR (2010)
Zahra Karimaghaloo, Mohak Shah, Simon J. Francis, Douglas L. Arnold, D. Louis Collins, Tal Arbel
Detection of Gad-Enhancing Lesions in Multiple Sclerosis Using Conditional Random Fields. MICCAI (3) (2010)
Yiming Xiao, Mohak Shah, Simon J. Francis, Douglas L. Arnold, Tal Arbel, D. Louis Collins
Optimal Gaussian Mixture Models of Tissue Intensities in Brain MRI of Patients with Multiple-Sclerosis. MLMI (2010)
Mohak Shah
Risk Bounds for Randomized Sample Compressed Classifiers. NIPS (2008)
Mohak Shah
Sample compression bounds for decision trees. ICML (2007)
Mohak Shah, Marina Sokolova, Stan Szpakowicz
Process-Specific Information for Learning Electronic Negotiation Outcomes. Fundam. Informaticae 74 (2-3) (2006)
François Laviolette, Mario Marchand, Mohak Shah
A PAC-Bayes approach to the Set Covering Machine. NIPS (2005)
François Laviolette, Mario Marchand, Mohak Shah
Margin-Sparsity Trade-Off for the Set Covering Machine. ECML (2005)
Mario Marchand, Mohak Shah
PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data. NIPS (2004)
Mario Marchand, Mohak Shah, John Shawe-Taylor, Marina Sokolova
The Set Covering Machine with Data-Dependent Half-Spaces. ICML (2003)