Vikas Verma

Publication Activity (10 Years)

Years Active: 1992-2024
Publications (10 Years): 32

Top Topics

Manifold Regularization

Unlabeled Instances

Top Venues

Neural Networks

Publications

Vikas Verma, Arun Malik, Isha Batra
Analyzing and Classifying Malware Types on Windows Platform using an Ensemble Machine Learning Approach. Int. J. Perform. Eng. 20 (5) (2024)
Debarshi Brahma, Amartya Bhattacharya, Suraj Nagaje Mahadev, Anmol Asati, Vikas Verma, Soma Biswas
Leveraging Out-of-Domain Data for Domain-Specific Prompt Tuning in Multi-Modal Fake News Detection. CoRR (2023)
Yingtian Zou, Vikas Verma, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi
MixupE: Understanding and improving Mixup from directional derivative perspective. UAI (2023)
Vikas Verma, Kenji Kawaguchi, Alex Lamb, Juho Kannala, Arno Solin, Yoshua Bengio, David Lopez-Paz
Interpolation consistency training for semi-supervised learning. Neural Networks 145 (2022)
Mojtaba Faramarzi, Mohammad Amini, Akilesh Badrinaaraayanan, Vikas Verma, Sarath Chandar
PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks. AAAI (2022)
Alexia Jolicoeur-Martineau, Alex Lamb, Vikas Verma, Aniket Didolkar
CNT (Conditioning on Noisy Targets): A new Algorithm for Leveraging Top-Down Feedback. CoRR (2022)
Vikas Verma, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi
MixupE: Understanding and Improving Mixup from Directional Derivative Perspective. CoRR (2022)
Vikas Verma, S. K. Sharma
Critical Analysis of Existing Punjabi Grammar Checker and a Proposed Hybrid Framework Involving Machine Learning and Rule-Base Criteria. ACM Trans. Asian Low Resour. Lang. Inf. Process. 21 (5) (2022)
Alex Lamb, Vikas Verma, Kenji Kawaguchi, Alexander Matyasko, Savya Khosla, Juho Kannala, Yoshua Bengio
Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy. Neural Networks 154 (2022)
Jisoo Jeong, Vikas Verma, Minsung Hyun, Juho Kannala, Nojun Kwak
Interpolation-Based Semi-Supervised Learning for Object Detection. CVPR (2021)
Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc V. Le
Towards Domain-Agnostic Contrastive Learning. ICML (2021)
Vikas Verma, Meng Qu, Kenji Kawaguchi, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang
GraphMix: Improved Training of GNNs for Semi-Supervised Learning. AAAI (2021)
Alex Lamb, Sherjil Ozair, Vikas Verma, David Ha
SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks. WACV (2020)
Jisoo Jeong, Vikas Verma, Minsung Hyun, Juho Kannala, Nojun Kwak
Interpolation-based semi-supervised learning for object detection. CoRR (2020)
Fan-Yun Sun, Jordan Hoffmann, Vikas Verma, Jian Tang
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization. ICLR (2020)
Vikas Verma, Minh-Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc V. Le
Towards Domain-Agnostic Contrastive Learning. CoRR (2020)
Mojtaba Faramarzi, Mohammad Amini, Akilesh Badrinaaraayanan, Vikas Verma, Sarath Chandar
PatchUp: A Regularization Technique for Convolutional Neural Networks. CoRR (2020)
Alex Lamb, Sherjil Ozair, Vikas Verma, David Ha
SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks. CoRR (2019)
Vikas Verma, Alex Lamb, Christopher Beckham, Amir Najafi, Ioannis Mitliagkas, David Lopez-Paz, Yoshua Bengio
Manifold Mixup: Better Representations by Interpolating Hidden States. ICML (2019)
Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz
Interpolation Consistency Training for Semi-Supervised Learning. CoRR (2019)
Christopher Beckham, Sina Honari, Vikas Verma, Alex Lamb, Farnoosh Ghadiri, R. Devon Hjelm, Yoshua Bengio, Chris Pal
On Adversarial Mixup Resynthesis. NeurIPS (2019)
Simon Guiroy, Vikas Verma, Christopher J. Pal
Towards Understanding Generalization in Gradient-Based Meta-Learning. CoRR (2019)
Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz
Interpolation Consistency Training for Semi-supervised Learning. IJCAI (2019)
Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio
Interpolated Adversarial Training: Achieving Robust Neural Networks Without Sacrificing Too Much Accuracy. AISec@CCS (2019)
Vikas Verma, Meng Qu, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang
GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning. CoRR (2019)
Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy. CoRR (2019)
Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R. Devon Hjelm, Christopher J. Pal
Adversarial Mixup Resynthesizers. DGS@ICLR (2019)
Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R. Devon Hjelm, Christopher J. Pal
Adversarial Mixup Resynthesizers. CoRR (2019)
Vikas Verma, Alex Lamb, Christopher Beckham, Aaron C. Courville, Ioannis Mitliagkas, Yoshua Bengio
Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer. CoRR (2018)
Stanislaw Jastrzebski, Devansh Arpit, Nicolas Ballas, Vikas Verma, Tong Che, Yoshua Bengio
Residual Connections Encourage Iterative Inference. ICLR (Poster) (2018)
Jason Jo, Vikas Verma, Yoshua Bengio
Modularity Matters: Learning Invariant Relational Reasoning Tasks. CoRR (2018)
Stanislaw Jastrzebski, Devansh Arpit, Nicolas Ballas, Vikas Verma, Tong Che, Yoshua Bengio
Residual Connections Encourage Iterative Inference. CoRR (2017)
Vikas Verma
Image Retrieval And Classification Using Local Feature Vectors. CoRR (2014)
Vikas Verma, D. Ghosh
Hand Gesture Reconstruction and Animation. IICAI (2005)
George Eby Mathew, Joseph Shields, Vikas Verma
QoS Based Pricing for Web Services. WISE Workshops (2004)
Vikas Verma, Malcolm Thurgur
A Fair Basis For Charge Back. Int. CMG Conference (1992)
Vikas Verma
A Meaningful Measure of Response Time for SLA. Int. CMG Conference (1992)