Vikram Saraph

2020

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Vikram Saraph trusts overall

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

1. Jonathan Baxter

Papers from Vikram Saraph's perspective

Ordered by how strongly the researchers Vikram Saraph 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. Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
3. In-datacenter performance analysis of a tensor processing unit
4. Matrix Factorization Techniques for Recommender Systems
5. Wide & Deep Learning for Recommender Systems
6. Deep Neural Networks for YouTube Recommendations
7. Neural Collaborative Filtering
8. Item-based collaborative filtering recommendation algorithms
9. Deep Interest Network for Click-Through Rate Prediction
10. Deep Learning Recommendation Model for Personalization and Recommendation Systems

Their papers

• DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference (2020) — 211 citations
• CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery (2020) — 47 citations