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2020 – today
- 2021
[j28]Nishchal K. Verma, Teena Sharma
, Sonal Dixit, Pooja Agrawal, Sourya Sengupta, Vikas Singh:
BIDEAL: A Toolbox for Bicluster Analysis - Generation, Visualization and Validation. SN Comput. Sci. 2(1): 24 (2021)- [c109]Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh:
Learning Invariant Representations using Inverse Contrastive Loss. AAAI 2021: 6582-6591 - [c108]Zihang Meng, Sathya N. Ravi, Vikas Singh:
Physarum Powered Differentiable Linear Programming Layers and Applications. AAAI 2021: 8939-8949 - [c107]Xingjian Zhen, Rudrasis Chakraborty, Liu Yang, Vikas Singh:
Flow-based Generative Models for Learning Manifold to Manifold Mappings. AAAI 2021: 11042-11052 - [c106]Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh:
Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention. AAAI 2021: 14138-14148 - [c105]Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Yongzhe Wang, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen:
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. CVPR 2021: 3825-3834 - [c104]Xingjian Zhen, Rudrasis Chakraborty, Vikas Singh:
Simpler Certified Radius Maximization by Propagating Covariances. CVPR 2021: 7292-7301 - [c103]Zihang Meng, Licheng Yu, Ning Zhang, Tamara L. Berg, Babak Damavandi, Vikas Singh, Amy Bearman:
Connecting What To Say With Where To Look by Modeling Human Attention Traces. CVPR 2021: 12679-12688 - [c102]Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi, Shailesh Acharya, Glenn M. Fung, Vikas Singh:
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling. ICML 2021: 12321-12332 - [i37]Teja Kanchinadam, Zihang Meng, Joseph Bockhorst, Vikas Singh, Glenn Fung:
Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center. CoRR abs/2102.00420 (2021) - [i36]Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh:
Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention. CoRR abs/2102.03902 (2021) - [i35]Aditya Kumar Akash, Vishnu Suresh Lokhande, Sathya N. Ravi, Vikas Singh:
Learning Invariant Representations using Inverse Contrastive Loss. CoRR abs/2102.08343 (2021) - [i34]Xingjian Zhen, Rudrasis Chakraborty, Vikas Singh:
Simpler Certified Radius Maximization by Propagating Covariances. CoRR abs/2104.05888 (2021) - [i33]Zihang Meng, Licheng Yu, Ning Zhang, Tamara L. Berg, Babak Damavandi, Vikas Singh, Amy Bearman:
Connecting What to Say With Where to Look by Modeling Human Attention Traces. CoRR abs/2105.05964 (2021) - [i32]Zihang Meng, Rudrasis Chakraborty, Vikas Singh:
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis. CoRR abs/2106.07479 (2021) - [i31]Zihang Meng, Vikas Singh, Sathya N. Ravi:
Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators. CoRR abs/2108.08891 (2021) - 2020
- [j27]Arthur F. A. Fernandes, Eduardo M. Turra, Érika R. de Alvarenga, Tiago L. Passafaro, Fernando B. Lopes, Gabriel F. O. Alves, Vikas Singh, Guilherme J. M. Rosa:
Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia. Comput. Electron. Agric. 170: 105274 (2020) - [j26]Arun K. Sharma, Dhan Jeet Singh, Vikas Singh, Nishchal K. Verma:
Aerodynamic Modeling of ATTAS Aircraft Using Mamdani Fuzzy Inference Network. IEEE Trans. Aerosp. Electron. Syst. 56(5): 3566-3576 (2020) - [c101]Sathya N. Ravi, Abhay Venkatesh, Glenn M. Fung, Vikas Singh:
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains. AAAI 2020: 5487-5494 - [c100]Vishnu Suresh Lokhande, Songwong Tasneeyapant, Abhay Venkatesh, Sathya N. Ravi, Vikas Singh:
Generating Accurate Pseudo-Labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations. CVPR 2020: 11432-11440 - [c99]Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh:
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret. ECCV (12) 2020: 365-381 - [c98]Wei Hao, Nicholas M. Vogt, Zihang Meng, Seong Jae Hwang, Rebecca L. Koscik, Sterling C. Johnson, Barbara B. Bendlin, Vikas Singh:
Learning Amyloid Pathology Progression from Longitudinal PIB-PET Images in Preclinical Alzheimer's Disease. ISBI 2020: 572-576 - [i30]Vishnu Suresh Lokhande, Aditya Kumar Akash, Sathya N. Ravi, Vikas Singh:
FairALM: Augmented Lagrangian Method for Training Fair Models with Little Regret. CoRR abs/2004.01355 (2020) - [i29]Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen:
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. CoRR abs/2004.14525 (2020) - [i28]Zihang Meng, Sathya N. Ravi, Vikas Singh:
Physarum Powered Differentiable Linear Programming Layers and Applications. CoRR abs/2004.14539 (2020) - [i27]Nishchal K. Verma, Teena Sharma, Sonal Dixit, Pooja Agrawal, Sourya Sengupta, Vikas Singh:
BIDEAL: A Toolbox for Bicluster Analysis - Generation, Visualization and Validation. CoRR abs/2007.13737 (2020) - [i26]Vikas Singh, Pooja Agrawal, Teena Sharma, Nishchal K. Verma:
Improved Adaptive Type-2 Fuzzy Filter with Exclusively Two Fuzzy Membership Function for Filtering Salt and Pepper Noise. CoRR abs/2008.04114 (2020) - [i25]Won Hwa Kim, Mona Jalal, Seong Jae Hwang, Sterling C. Johnson, Vikas Singh:
Online Graph Completion: Multivariate Signal Recovery in Computer Vision. CoRR abs/2008.05060 (2020) - [i24]Vikas Singh, Homanga Bharadhwaj, Nishchal K. Verma:
A Bayesian Approach with Type-2 Student-tMembership Function for T-S Model Identification. CoRR abs/2009.00822 (2020) - [i23]Xingjian Zhen, Rudrasis Chakraborty, Liu Yang, Vikas Singh:
Flow-based Generative Models for Learning Manifold to Manifold Mappings. CoRR abs/2012.10013 (2020)
2010 – 2019
- 2019
- [j25]Seong Jae Hwang, Nagesh Adluru, Won Hwa Kim, Sterling C. Johnson, Barbara B. Bendlin, Vikas Singh:
Associations Between Positron Emission Tomography Amyloid Pathology and Diffusion Tensor Imaging Brain Connectivity in Pre-Clinical Alzheimer's Disease. Brain Connect. 9(2): 162-173 (2019) - [c97]Sathya N. Ravi, Tuan Dinh, Vishnu Suresh Lokhande, Vikas Singh:
Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence. AAAI 2019: 4772-4779 - [c96]Yunyang Xiong, Hyunwoo J. Kim, Vikas Singh:
Mixed Effects Neural Networks (MeNets) With Applications to Gaze Estimation. CVPR 2019: 7743-7752 - [c95]Teena Sharma, Vikas Singh, Siddharth Sudhakaran, Nishchal K. Verma:
Fuzzy based Pooling in Convolutional Neural Network for Image Classification. FUZZ-IEEE 2019: 1-6 - [c94]Vikas Singh, Teena Sharma, Nishchal K. Verma, Yan Cui:
Feature Ranking using Robust Fuzzy Score Function for Gene Expression Data. FUZZ-IEEE 2019: 1-6 - [c93]Yunyang Xiong, Ronak Mehta, Vikas Singh:
Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help? ICCV 2019: 1901-1910 - [c92]Yiyou Sun, Sathya N. Ravi, Vikas Singh:
Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks. ICCV 2019: 4937-4946 - [c91]Ronak Mehta, Rudrasis Chakraborty, Vikas Singh, Yunyang Xiong:
Scaling Recurrent Models via Orthogonal Approximations in Tensor Trains. ICCV 2019: 10570-10578 - [c90]Haoliang Sun, Ronak Mehta, Hao Henry Zhou, Zhichun Huang, Sterling C. Johnson, Vivek Prabhakaran, Vikas Singh:
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer. ICCV 2019: 10610-10619 - [c89]Rudrasis Chakraborty, Xingjian Zhen, Nicholas Vogt, Barbara B. Bendlin, Vikas Singh:
Dilated Convolutional Neural Networks for Sequential Manifold-Valued Data. ICCV 2019: 10620-10630 - [c88]Seong Jae Hwang, Zirui Tao, Vikas Singh, Won Hwa Kim:
Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples With Applications to Neuroimaging. ICCV 2019: 10691-10700 - [c87]Yunyang Xiong, Hyunwoo J. Kim, Bhargav Tangirala, Ronak Mehta, Sterling C. Johnson, Vikas Singh:
On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging. IPMI 2019: 99-111 - [c86]Seong Jae Hwang, Ronak Mehta, Hyunwoo J. Kim, Sterling C. Johnson, Vikas Singh:
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Applications to Normative Modeling in Neuroimaging. UAI 2019: 809-819 - [i22]Yunyang Xiong, Ronak Mehta, Vikas Singh:
Resource Constrained Neural Network Architecture Search. CoRR abs/1904.03786 (2019) - [i21]Owen Levin, Zihang Meng, Vikas Singh, Xiaojin Zhu:
Fooling Computer Vision into Inferring the Wrong Body Mass Index. CoRR abs/1905.06916 (2019) - [i20]Haoliang Sun, Ronak Mehta, Hao Henry Zhou, Zhichun Huang, Sterling C. Johnson, Vivek Prabhakaran, Vikas Singh:
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer. CoRR abs/1908.08074 (2019) - [i19]Vishnu Suresh Lokhande, Sathya N. Ravi, Songwong Tasneeyapant, Abhay Venkatesh, Vikas Singh:
Generating Accurate Pseudo-labels via Hermite Polynomials for SSL Confidently. CoRR abs/1909.05479 (2019) - [i18]Sathya N. Ravi, Abhay Venkatesh, Glenn Moo Fung, Vikas Singh:
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization offers Significant Performance and Efficiency Gains. CoRR abs/1909.12398 (2019) - [i17]Xingjian Zhen, Rudrasis Chakraborty, Nicholas Vogt, Barbara B. Bendlin, Vikas Singh:
Dilated Convolutional Neural Networks for Sequential Manifold-valued Data. CoRR abs/1910.02206 (2019) - [i16]Vikas Singh, Nishchal K. Verma:
An Entropy-based Variable Feature Weighted Fuzzy k-Means Algorithm for High Dimensional Data. CoRR abs/1912.11209 (2019) - [i15]Vikas Singh, Nishchal K. Verma:
mRMR-DNN with Transfer Learning for IntelligentFault Diagnosis of Rotating Machines. CoRR abs/1912.11235 (2019) - 2018
- [j24]Vikas Singh, Raghav Dev, Narendra Kumar Dhar, Pooja Agrawal, Nishchal K. Verma:
Adaptive Type-2 Fuzzy Approach for Filtering Salt and Pepper Noise in Grayscale Images. IEEE Trans. Fuzzy Syst. 26(5): 3170-3176 (2018) - [c85]Seong Jae Hwang, Sathya N. Ravi, Zirui Tao, Hyunwoo J. Kim, Maxwell D. Collins, Vikas Singh:
Tensorize, Factorize and Regularize: Robust Visual Relationship Learning. CVPR 2018: 1014-1023 - [c84]Lopamudra Mukherjee, Sathya N. Ravi, Jiming Peng, Vikas Singh:
A Biresolution Spectral Framework for Product Quantization. CVPR 2018: 3329-3338 - [c83]Zihang Meng, Nagesh Adluru, Hyunwoo J. Kim, Glenn Fung, Vikas Singh:
Efficient Relative Attribute Learning Using Graph Neural Networks. ECCV (14) 2018: 575-590 - [c82]Vikas Singh, Harsh Vardhan, Nishchal K. Verma, Yan Cui:
Optimal Feature Selection using Fuzzy Combination of Feature Subset for Transcriptome Data. FUZZ-IEEE 2018: 1-8 - [c81]Seetaram Maurya, Vikas Singh, Sonal Dixit, Nishchal K. Verma, Al Salour, Jie Liu:
Fusion of Low-level Features with Stacked Autoencoder for Condition based Monitoring of Machines. ICPHM 2018: 1-8 - [c80]Gaurav Saraswat, Vikas Singh, Nishchal K. Verma, Al Salour, Jie Liu:
Prognosis of Diesel Engine (MBT) Using Feature Extraction Techniques: A Comparative Study. ICPHM 2018: 1-6 - [c79]Rogers Jeffrey Leo John, Jignesh M. Patel, Andrew L. Alexander, Vikas Singh, Nagesh Adluru:
A Natural Language Interface for Dissemination of Reproducible Biomedical Data Science. MICCAI (4) 2018: 197-205 - [c78]Rudrasis Chakraborty, Chun-Hao Yang, Xingjian Zhen, Monami Banerjee, Derek Archer, David E. Vaillancourt, Vikas Singh, Baba C. Vemuri:
A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices. NeurIPS 2018: 8897-8908 - [i14]Sathya N. Ravi, Tuan Dinh, Vishnu Sai Rao Lokhande, Vikas Singh:
Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision. CoRR abs/1803.06453 (2018) - [i13]Sathya N. Ravi, Ronak Mehta, Vikas Singh:
Robust Blind Deconvolution via Mirror Descent. CoRR abs/1803.08137 (2018) - [i12]Seong Jae Hwang, Ronak Mehta, Vikas Singh:
Sampling-free Uncertainty Estimation in Gated Recurrent Units with Exponential Families. CoRR abs/1804.07351 (2018) - [i11]Rudrasis Chakraborty, Chun-Hao Yang, Xingjian Zhen, Monami Banerjee, Derek Archer, David E. Vaillancourt, Vikas Singh, Baba C. Vemuri:
Statistical Recurrent Models on Manifold valued Data. CoRR abs/1805.11204 (2018) - [i10]Hao Henry Zhou, Yunyang Xiong, Vikas Singh:
Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty. CoRR abs/1806.03563 (2018) - [i9]Seong Jae Hwang, Zirui Tao, Won Hwa Kim, Vikas Singh:
Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples with Applications to Neuroimaging. CoRR abs/1811.09897 (2018) - 2017
- [j23]Felipe Gutierrez-Barragan, Vamsi K. Ithapu, Chris Hinrichs, Camille Maumet, Sterling C. Johnson, Thomas E. Nichols, Vikas Singh:
Accelerating permutation testing in voxel-wise analysis through subspace tracking: A new plugin for SnPM. NeuroImage 159: 79-98 (2017) - [c77]Vamsi K. Ithapu, Risi Kondor, Sterling C. Johnson, Vikas Singh:
The Incremental Multiresolution Matrix Factorization Algorithm. CVPR 2017: 692-701 - [c76]Ligang Zheng, Hyunwoo J. Kim, Nagesh Adluru, Michael A. Newton, Vikas Singh:
Riemannian Variance Filtering: An Independent Filtering Scheme for Statistical Tests on Manifold-Valued Data. CVPR Workshops 2017: 699-708 - [c75]Sathya N. Ravi, Yunyang Xiong, Lopamudra Mukherjee, Vikas Singh:
Filter Flow Made Practical: Massively Parallel and Lock-Free. CVPR 2017: 5009-5018 - [c74]Won Hwa Kim, Mona Jalal, Seong Jae Hwang, Sterling C. Johnson, Vikas Singh:
Online Graph Completion: Multivariate Signal Recovery in Computer Vision. CVPR 2017: 5019-5027 - [c73]Hyunwoo J. Kim, Nagesh Adluru, Heemanshu Suri, Baba C. Vemuri, Sterling C. Johnson, Vikas Singh:
Riemannian Nonlinear Mixed Effects Models: Analyzing Longitudinal Deformations in Neuroimaging. CVPR 2017: 5777-5786 - [c72]Rudrasis Chakraborty, Vikas Singh, Nagesh Adluru, Baba C. Vemuri:
A Geometric Framework for Statistical Analysis of Trajectories with Distinct Temporal Spans. ICCV 2017: 172-181 - [c71]Hao Henry Zhou, Yilin Zhang, Vamsi K. Ithapu, Sterling C. Johnson, Grace Wahba, Vikas Singh:
When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, $\ell_2$-consistency and Neuroscience Applications. ICML 2017: 4170-4179 - [c70]Gregory Plumb, Lindsay Clark, Sterling C. Johnson, Vikas Singh:
Modeling Cognitive Trends in Preclinical Alzheimer's Disease (AD) via Distributions over Permutations. MICCAI (3) 2017: 683-691 - [p1]Vamsi K. Ithapu, Vikas Singh, Sterling C. Johnson:
Randomized Deep Learning Methods for Clinical Trial Enrichment and Design in Alzheimer's Disease. Deep Learning for Medical Image Analysis 2017: 341-378 - [i8]Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh:
On architectural choices in deep learning: From network structure to gradient convergence and parameter estimation. CoRR abs/1702.08670 (2017) - [i7]Felipe Gutierrez-Barragan, Vamsi K. Ithapu, Chris Hinrichs, Camille Maumet, Sterling C. Johnson, Thomas E. Nichols, Vikas Singh:
Accelerating Permutation Testing in Voxel-wise Analysis through Subspace Tracking: A new plugin for SnPM. CoRR abs/1703.01506 (2017) - [i6]Vamsi K. Ithapu, Risi Kondor, Sterling C. Johnson, Vikas Singh:
The Incremental Multiresolution Matrix Factorization Algorithm. CoRR abs/1705.05804 (2017) - [i5]Sathya N. Ravi, Maxwell D. Collins, Vikas Singh:
A Deterministic Nonsmooth Frank Wolfe Algorithm with Coreset Guarantees. CoRR abs/1708.06714 (2017) - [i4]Ronak Mehta, Hyunwoo J. Kim, Shulei Wang, Sterling C. Johnson, Ming Yuan, Vikas Singh:
Finding Differentially Covarying Needles in a Temporally Evolving Haystack: A Scan Statistics Perspective. CoRR abs/1711.07575 (2017) - 2016
- [j22]Margam Madhusudhan, Vikas Singh:
Integrated library management systems: Comparative analysis of Koha, Libsys, NewGenLib, and Virtua. Electron. Libr. 34(2): 223-249 (2016) - [c69]Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh:
On the interplay of network structure and gradient convergence in deep learning. Allerton 2016: 488-495 - [c68]Vikas Singh, Nikhil Baranwal, Rahul Kumar Sevakula, Nishchal K. Verma, Yan Cui:
Layerwise feature selection in Stacked Sparse Auto-Encoder for tumor type prediction. BIBM 2016: 1542-1548 - [c67]Won Hwa Kim, Hyunwoo J. Kim, Nagesh Adluru, Vikas Singh:
Latent Variable Graphical Model Selection Using Harmonic Analysis: Applications to the Human Connectome Project (HCP). CVPR 2016: 2443-2451 - [c66]Seong Jae Hwang, Nagesh Adluru, Maxwell D. Collins, Sathya N. Ravi, Barbara B. Bendlin, Sterling C. Johnson, Vikas Singh:
Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks. CVPR 2016: 2517-2525 - [c65]Won Hwa Kim, Seong Jae Hwang, Nagesh Adluru, Sterling C. Johnson, Vikas Singh:
Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimaging. ECCV (6) 2016: 188-205 - [c64]Lopamudra Mukherjee, Jiming Peng, Trevor Sigmund, Vikas Singh:
Network Flow Formulations for Learning Binary Hashing. ECCV (5) 2016: 366-381 - [c63]Hyunwoo J. Kim, Brandon M. Smith, Nagesh Adluru, Charles R. Dyer, Sterling C. Johnson, Vikas Singh:
Abundant Inverse Regression Using Sufficient Reduction and Its Applications. ECCV (3) 2016: 570-584 - [c62]Vikas Singh, Rahul K. Gupta, Rahul Kumar Sevakula, Nishchal K. Verma:
Comparative analysis of Gaussian mixture model, logistic regression and random forest for big data classification using map reduce. ICIIS 2016: 333-338 - [c61]Sathya N. Ravi, Vamsi K. Ithapu, Sterling C. Johnson, Vikas Singh:
Experimental Design on a Budget for Sparse Linear Models and Applications. ICML 2016: 583-592 - [c60]Matt Straayer, Jim Bales, Dwight Birdsall, Denis C. Daly, Phillip Elliott, Bill Foley, Roy Mason, Vikas Singh, Xuejin Wang:
27.5 A 4GS/s time-interleaved RF ADC in 65nm CMOS with 4GHz input bandwidth. ISSCC 2016: 464-465 - [c59]Hao Henry Zhou, Vamsi K. Ithapu, Sathya Narayanan Ravi, Vikas Singh, Grace Wahba, Sterling C. Johnson:
Hypothesis Testing in Unsupervised Domain Adaptation with Applications in Alzheimer's Disease. NIPS 2016: 2496-2504 - [c58]Drew Davidson, Hao Wu, Robert Jellinek, Vikas Singh, Thomas Ristenpart:
Controlling UAVs with Sensor Input Spoofing Attacks. WOOT 2016 - 2015
- [j21]Gregory Plumb, Deepti Pachauri, Risi Kondor, Vikas Singh:
SnFFT: a Julia toolkit for Fourier analysis of functions over permutations. J. Mach. Learn. Res. 16: 3469-3473 (2015) - [j20]Won Hwa Kim, Nagesh Adluru, Moo K. Chung, Ozioma C. Okonkwo, Sterling C. Johnson, Barbara B. Bendlin, Vikas Singh:
Multi-resolution statistical analysis of brain connectivity graphs in preclinical Alzheimer's disease. NeuroImage 118: 103-117 (2015) - [c57]Jia Xu, Lopamudra Mukherjee, Yin Li, Jamieson Warner, James M. Rehg, Vikas Singh:
Gaze-enabled egocentric video summarization via constrained submodular maximization. CVPR 2015: 2235-2244 - [c56]Won Hwa Kim, Barbara B. Bendlin, Moo K. Chung, Sterling C. Johnson, Vikas Singh:
Statistical inference models for image datasets with systematic variations. CVPR 2015: 4795-4803 - [c55]Won Hwa Kim, Sathya N. Ravi, Sterling C. Johnson, Ozioma C. Okonkwo, Vikas Singh:
On Statistical Analysis of Neuroimages with Imperfect Registration. ICCV 2015: 666-674 - [c54]Seong Jae Hwang, Maxwell D. Collins, Sathya N. Ravi, Vamsi K. Ithapu, Nagesh Adluru, Sterling C. Johnson, Vikas Singh:
A Projection Free Method for Generalized Eigenvalue Problem with a Nonsmooth Regularizer. ICCV 2015: 1841-1849 - [c53]Hyunwoo J. Kim, Nagesh Adluru, Monami Banerjee, Baba C. Vemuri, Vikas Singh:
Interpolation on the Manifold of K Component GMMs. ICCV 2015: 2884-2892 - [c52]Lopamudra Mukherjee, Sathya N. Ravi, Vamsi K. Ithapu, Tyler Holmes, Vikas Singh:
An NMF Perspective on Binary Hashing. ICCV 2015: 4184-4192 - [c51]Hyunwoo J. Kim, Jia Xu, Baba C. Vemuri, Vikas Singh:
Manifold-valued Dirichlet Processes. ICML 2015: 1199-1208 - [c50]Won Hwa Kim, Vikas Singh, Moo K. Chung, Nagesh Adluru, Barbara B. Bendlin, Sterling C. Johnson:
Multi-resolution statistical analysis on graph structured data in neuroimaging. ISBI 2015: 1548-1551 - [i3]Chris Hinrichs, Vamsi K. Ithapu, Qinyuan Sun, Sterling C. Johnson, Vikas Singh:
Speeding up Permutation Testing in Neuroimaging. CoRR abs/1502.03536 (2015) - [i2]Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh:
Convergence of gradient based pre-training in Denoising autoencoders. CoRR abs/1502.03537 (2015) - [i1]Vamsi K. Ithapu, Sathya N. Ravi, Vikas Singh:
On the interplay of network structure and gradient convergence in deep learning. CoRR abs/1511.05297 (2015) - 2014
- [j19]Won Hwa Kim, Vikas Singh, Moo K. Chung, Chris Hinrichs, Deepti Pachauri, Ozioma C. Okonkwo, Sterling C. Johnson:
Multi-resolutional shape features via non-Euclidean wavelets: Applications to statistical analysis of cortical thickness. NeuroImage 93: 107-123 (2014) - [c49]Hyunwoo J. Kim, Barbara B. Bendlin, Nagesh Adluru, Maxwell D. Collins, Moo K. Chung, Sterling C. Johnson, Richard J. Davidson, Vikas Singh:
Multivariate General Linear Models (MGLM) on Riemannian Manifolds with Applications to Statistical Analysis of Diffusion Weighted Images. CVPR 2014: 2705-2712 - [c48]Hyunwoo J. Kim, Nagesh Adluru, Barbara B. Bendlin, Sterling C. Johnson, Baba C. Vemuri, Vikas Singh:
Canonical Correlation Analysis on Riemannian Manifolds and Its Applications. ECCV (2) 2014: 251-267 - [c47]Maxwell D. Collins, Ji Liu, Jia Xu, Lopamudra Mukherjee, Vikas Singh:
Spectral Clustering with a Convex Regularizer on Millions of Images. ECCV (3) 2014: 282-298 - [c46]Vamsi K. Ithapu, Vikas Singh, Ozioma C. Okonkwo, Sterling C. Johnson:
Randomized Denoising Autoencoders for Smaller and Efficient Imaging Based AD Clinical Trials. MICCAI (2) 2014: 470-478 - [c45]Deepti Pachauri, Risi Kondor, Gautam Sargur, Vikas Singh:
Permutation Diffusion Maps (PDM) with Application to the Image Association Problem in Computer Vision. NIPS 2014: 541-549 - 2013
- [j18]Svyatoslav Vergun, Alok Deshpande, Timothy B. Meier, Jie Song, Dana Tudorascu, Veena A. Nair, Vikas Singh, Bharat B. Biswal, Mary Elizabeth Meyerand, Rasmus M. Birn, Vivek Prabhakaran:
Characterizing Functional Connectivity Differences in Aging Adults using Machine Learning on Resting State fMRI Data. Frontiers Comput. Neurosci. 7: 38 (2013) - [c44]Jia Xu, Maxwell D. Collins, Vikas Singh:
Incorporating User Interaction and Topological Constraints within Contour Completion via Discrete Calculus. CVPR 2013: 1886-1893 - [c43]Won Hwa Kim, Moo K. Chung, Vikas Singh:
Multi-resolution Shape Analysis via Non-Euclidean Wavelets: Applications to Mesh Segmentation and Surface Alignment Problems. CVPR 2013: 2139-2146 - [c42]Jia Xu, Vamsi K. Ithapu, Lopamudra Mukherjee, James M. Rehg, Vikas Singh:
GOSUS: Grassmannian Online Subspace Updates with Structured-Sparsity. ICCV 2013: 3376-3383 - [c41]Yogesh Darwhekar, Evgeniy Braginskiy, Koby Levy, Abhishek Agrawal, Vikas Singh, Ronen Issac, Ofer Blonskey, Ofer Adler, Yoav Benkuzari, Matan Ben-Shachar, Srikanth Manian, Apu Sivadas, Subhashish Mukherjee, Gangadhar Burra, Nir Tal, Yariv Shlivinski, Guy Bitton, Sreekiran Samala:
A 45nm CMOS near-field communication radio with 0.15A/m RX sensitivity and 4mA current consumption in card emulation mode. ISSCC 2013: 440-441 - [c40]Won Hwa Kim, Nagesh Adluru, Moo K. Chung, Sylvia Charchut, Johnson J. GadElkarim, Lori L. Altshuler, Teena Moody, Anand R. Kumar, Vikas Singh, Alex D. Leow:
Multi-resolutional Brain Network Filtering and Analysis via Wavelets on Non-Euclidean Space. MICCAI (3) 2013: 643-651 - [c39]Chris Hinrichs, Vamsi K. Ithapu, Qinyuan Sun, Sterling C. Johnson, Vikas Singh:
Speeding up Permutation Testing in Neuroimaging. NIPS 2013: 890-898 - [c38]Deepti Pachauri, Risi Kondor, Vikas Singh:
Solving the multi-way matching problem by permutation synchronization. NIPS 2013: 1860-1868 - 2012
- [j17]Jiming Peng, Lopamudra Mukherjee, Vikas Singh, Dale Schuurmans, Linli Xu:
An efficient algorithm for maximal margin clustering. J. Glob. Optim. 52(1): 123-137 (2012) - [j16]Vikas Singh, Deepak Singh, Ritu Tiwari, Anupam Shukla:
MDABC: Motif Discovery Using Artificial Bee Colony Algorithm. J. Inf. Technol. Res. 5(4): 30-47 (2012) - [j15]Vikas Singh, Nagendra Krishnapura, Shanthi Pavan, Baradwaj Vigraham, Debasish Behera, Nimit Nigania:
A 16 MHz BW 75 dB DR CT ΔΣ ADC Compensated for More Than One Cycle Excess Loop Delay. IEEE J. Solid State Circuits 47(8): 1884-1895 (2012) - [c37]