Anil Kag

According to our database, Anil Kag authored at least 15 papers between 2018 and 2024.

Collaborative distances:

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

2024

TextCraftor: Your Text Encoder Can be Image Quality Controller.

Yanyu Li, Xian Liu, Anil Kag, Ju Hu, Yerlan Idelbayev, Dhritiman Sagar, Yanzhi Wang, Sergey Tulyakov, Jian Ren

CoRR, 2024

Snap Video: Scaled Spatiotemporal Transformers for Text-to-Video Synthesis.

Willi Menapace, Aliaksandr Siarohin, Ivan Skorokhodov, Ekaterina Deyneka, Tsai-Shien Chen, Anil Kag, Yuwei Fang, Aleksei Stoliar, Elisa Ricci, Jian Ren, Sergey Tulyakov

CoRR, 2024

2023

Efficient Edge Inference by Selective Query.

Anil Kag, Igor Fedorov, Aditya Gangrade, Paul N. Whatmough, Venkatesh Saligrama

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Scaffolding a Student to Instill Knowledge.

Anil Kag, Durmus Alp Emre Acar, Aditya Gangrade, Venkatesh Saligrama

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Condensing CNNs with Partial Differential Equations.

Anil Kag, Venkatesh Saligrama

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Online Selective Classification with Limited Feedback.

Aditya Gangrade, Anil Kag, Ashok Cutkosky, Venkatesh Saligrama

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Training Recurrent Neural Networks via Forward Propagation Through Time.

Anil Kag, Venkatesh Saligrama

Proceedings of the 38th International Conference on Machine Learning, 2021

Time Adaptive Recurrent Neural Network.

Anil Kag, Venkatesh Saligrama

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Selective Classification via One-Sided Prediction.

Aditya Gangrade, Anil Kag, Venkatesh Saligrama

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?

Anil Kag, Ziming Zhang, Venkatesh Saligrama

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

RNNs Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?

Anil Kag, Ziming Zhang, Venkatesh Saligrama

CoRR, 2019

Equilibrated Recurrent Neural Network: Neuronal Time-Delayed Self-Feedback Improves Accuracy and Stability.

Ziming Zhang, Anil Kag, Alan Sullivan, Venkatesh Saligrama

CoRR, 2019

BLAS-on-flash: An Efficient Alternative for Large Scale ML Training and Inference?

Suhas Jayaram Subramanya, Harsha Vardhan Simhadri, Srajan Garg, Anil Kag, Venkatesh Balasubramanian

Proceedings of the 16th USENIX Symposium on Networked Systems Design and Implementation, 2019

2018

Parabel: Partitioned Label Trees for Extreme Classification with Application to Dynamic Search Advertising.

Yashoteja Prabhu, Anil Kag, Shrutendra Harsola, Rahul Agrawal, Manik Varma

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Extreme Multi-label Learning with Label Features for Warm-start Tagging, Ranking & Recommendation.

Yashoteja Prabhu, Anil Kag, Shilpa Gopinath, Kunal Dahiya, Shrutendra Harsola, Rahul Agrawal, Manik Varma

Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018