Pramod K. Varshney

Artificial Intelligence · 1997–2020

A researcher in the Science corpus: 17 papers; trusts 68 researchers and is trusted by 33 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 89 citations into it
• Computer Networks and Communications — 81 citations into it; #792 of 9,886 by trust here, #843 by citations
• Safety, Robustness & Interpretability — 32 citations into it
• Electrical and Electronic Engineering — 30 citations into it
• Computer Vision and Pattern Recognition — 24 citations into it
• Computational Mechanics — 19 citations into it; #8,438 of 10,001 by trust here, #6,041 by citations
• Optimization & Training — 18 citations into it
• Signal Processing — 17 citations into it

Whom Pramod K. Varshney trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Andrew Howard
2. John N. Tsitsiklis
3. Alex Krizhevsky
4. Haowen Chan
5. Geoffrey E. Hinton
6. Adrian Perrig
7. Deborah Estrin
8. Yoshua Bengio
9. Diederik P. Kingma
10. Christian Szegedy

Who trusts Pramod K. Varshney overall

1. Raghavendra V. Kulkarni
2. Seyit Ahmet Camtepe
3. Donggang Liu
4. M. A. Güvensan
5. Sujesha Sudevalayam
6. Urs Hunkeler
7. Wenliang Du
8. Satyajayant Misra
9. Ganesh Kumar Venayagamoorthy
10. Tifenn Rault

Papers from Pramod K. Varshney's perspective

Ordered by how strongly the researchers Pramod K. Varshney trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. ImageNet: A large-scale hierarchical image database
4. Learning Multiple Layers of Features from Tiny Images
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. GENERATIVE ADVERSARIAL NETS
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning: Principals, Recent Advances, and Applications (2020) — 339 citations
• A pairwise key predistribution scheme for wireless sensor networks (2005) — 1,122 citations
• TWOACK: preventing selfishness in mobile ad hoc networks (2005) — 382 citations
• Channel aware decision fusion in wireless sensor networks (2004) — 431 citations
• Collaborative Spectrum Sensing in the Presence of Byzantine Attacks in Cognitive Radio Networks (2010) — 351 citations
• Anomalous Instance Detection in Deep Learning: A Survey (2020) — 48 citations
• Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory (2018) — 24 citations
• Decision Tree Design for Classification in Crowdsourcing Systems (2018) — 10 citations
• Low-Dimensional Approach for Reconstruction of Airfoil Data via Compressive Sensing (2015) — 76 citations
• Fusion of decisions transmitted over Rayleigh fading channels in wireless sensor networks (2006) — 325 citations
• Data-aggregation techniques in sensor networks: a survey (2006) — 1,035 citations
• Decision tree regression for soft classification of remote sensing data (2005) — 589 citations
• Energy-efficient deployment of Intelligent Mobile sensor networks (2005) — 453 citations
• QoS Support in Wireless Sensor Networks: A Survey (2004) — 627 citations
• A key management scheme for wireless sensor networks using deployment knowledge (2004) — 1,054 citations
• A pairwise key pre-distribution scheme for wireless sensor networks (2003) — 1,250 citations
• Distributed detection with multiple sensors I. Fundamentals (1997)