Rakesh Shivanna

According to our database, Rakesh Shivanna authored at least 10 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMs.

Ankit Singh Rawat, Veeranjaneyulu Sadhanala, Afshin Rostamizadeh, Ayan Chakrabarti, Wittawat Jitkrittum, Vladimir Feinberg, Seungyeon Kim, Hrayr Harutyunyan, Nikunj Saunshi, Zachary Nado, Rakesh Shivanna, Sashank J. Reddi, Aditya Krishna Menon, Rohan Anil, Sanjiv Kumar

CoRR, 2024

Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries.

Kiran Vodrahalli, Santiago Ontanon, Nilesh Tripuraneni, Kelvin Xu, Sanil Jain, Rakesh Shivanna, Jeffrey Hui, Nishanth Dikkala, Mehran Kazemi, Bahare Fatemi, Rohan Anil, Ethan Dyer, Siamak Shakeri, Roopali Vij, Harsh Mehta, Vinay V. Ramasesh, Quoc Le, Ed H. Chi, Yifeng Lu, Orhan Firat, Angeliki Lazaridou, Jean-Baptiste Lespiau, Nithya Attaluri, Kate Olszewska

CoRR, 2024

2022

Algorithms for Efficiently Learning Low-Rank Neural Networks.

Kiran Vodrahalli, Rakesh Shivanna, Maheswaran Sathiamoorthy, Sagar Jain, Ed H. Chi

CoRR, 2022

On the Factory Floor: ML Engineering for Industrial-Scale Ads Recommendation Models.

Rohan Anil, Sandra Gadanho, Da Huang, Nijith Jacob, Zhuoshu Li, Dong Lin, Todd Phillips, Cristina Pop, Kevin Regan, Gil I. Shamir, Rakesh Shivanna, Qiqi Yan

Proceedings of the 5th Workshop on Online Recommender Systems and User Modeling co-located with the 16th ACM Conference on Recommender Systems, 2022

2021

DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems.

Ruoxi Wang, Rakesh Shivanna, Derek Zhiyuan Cheng, Sagar Jain, Dong Lin, Lichan Hong, Ed H. Chi

Proceedings of the WWW '21: The Web Conference 2021, 2021

2020

DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems.

Ruoxi Wang, Rakesh Shivanna, Derek Zhiyuan Cheng, Sagar Jain, Dong Lin, Lichan Hong, Ed H. Chi

CoRR, 2020

Understanding and Improving Knowledge Distillation.

Jiaxi Tang, Rakesh Shivanna, Zhe Zhao, Dong Lin, Anima Singh, Ed H. Chi, Sagar Jain

CoRR, 2020

2019

How Many Pairwise Preferences Do We Need to Rank a Graph Consistently?

Aadirupa Saha, Rakesh Shivanna, Chiranjib Bhattacharyya

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2015

Spectral Norm Regularization of Orthonormal Representations for Graph Transduction.

Rakesh Shivanna, Bibaswan K. Chatterjee, Raman Sankaran, Chiranjib Bhattacharyya, Francis R. Bach

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Learning on graphs using Orthonormal Representation is Statistically Consistent.

Rakesh Shivanna, Chiranjib Bhattacharyya

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014