Kunal Dahiya

Indian Institute of Technology Delhi

H-index: 8

Asia-India

About Kunal Dahiya

Kunal Dahiya, With an exceptional h-index of 8 and a recent h-index of 8 (since 2020), a distinguished researcher at Indian Institute of Technology Delhi, specializes in the field of Machine Learning, Deep Learning, Extreme Classification.

His recent articles reflect a diverse array of research interests and contributions to the field:

The Challenge of Multiple Thermal Comfort Prediction Models: Is TSV Enough?

Ngame: Negative mining-aware mini-batching for extreme classification

Mitigating Trade-Off in Unlicensed Network Optimization Through Machine Learning and Context Awareness

Deep encoders with auxiliary parameters for extreme classification

LTE-LAA cell selection through operator data learning and numerosity reduction

Building matters: Spatial variability in machine learning based thermal comfort prediction in winters

Multi-modal extreme classification

Are You Comfortable Now: Deep Learning the Temporal Variation in Thermal Comfort in Winters

Kunal Dahiya Information

University	Indian Institute of Technology Delhi
Position	PhD Student
Citations(all)	586
Citations(since 2020)	558
Cited By	150
hIndex(all)	8
hIndex(since 2020)	8
i10Index(all)	8
i10Index(since 2020)	8
Email	Access Email
University Profile Page	Indian Institute of Technology Delhi
Google Scholar	View Google Scholar Profile

Kunal Dahiya Skills & Research Interests

Machine Learning

Deep Learning

Extreme Classification

Top articles of Kunal Dahiya

Title	Journal	Author(s)	Publication Date
The Challenge of Multiple Thermal Comfort Prediction Models: Is TSV Enough?	Buildings	Betty Lala Amogh Biju Vanshita Anmol Rastogi Kunal Dahiya ...	2023/3/28
Ngame: Negative mining-aware mini-batching for extreme classification		Kunal Dahiya Nilesh Gupta Deepak Saini Akshay Soni Yajun Wang ...	2023/2/27
Mitigating Trade-Off in Unlicensed Network Optimization Through Machine Learning and Context Awareness	IEEE Access	Srikant Manas Kala Vanlin Sathya Kunal Dahiya Teruo Higashino Hirozumi Yamaguchi	2023/1/10
Deep encoders with auxiliary parameters for extreme classification		Kunal Dahiya Sachin Yadav Sushant Sondhi Deepak Saini Sonu Mehta ...	2023/8/6
LTE-LAA cell selection through operator data learning and numerosity reduction	Pervasive and Mobile Computing	Srikant Manas Kala Kunal Dahiya Vanlin Sathya Teruo Higashino Hirozumi Yamaguchi	2022/7/1
Building matters: Spatial variability in machine learning based thermal comfort prediction in winters		Betty Lala Srikant Manas Kala Anmol Rastogi Kunal Dahiya Hirozumi Yamaguchi ...	2022/6/20
Multi-modal extreme classification		Anshul Mittal Kunal Dahiya Shreya Malani Janani Ramaswamy Seba Kuruvilla ...	2022
Are You Comfortable Now: Deep Learning the Temporal Variation in Thermal Comfort in Winters		Betty Lala Srikant Manas Kala Anmol Rastogi Kunal Dahiya Aya Hagishima	2022/10/9
Identification and analysis of a unique cell selection phenomenon in public unlicensed cellular networks through machine learning	IEEE Access	Srikant Manas Kala Vanlin Sathya Kunal Dahiya Teruo Higashino Hirozumi Yamaguchi	2022/8/17
Decaf: Deep extreme classification with label features		Anshul Mittal Kunal Dahiya Sheshansh Agrawal Deepak Saini Sumeet Agarwal ...	2021/3/8
Deepxml: A deep extreme multi-label learning framework applied to short text documents		Kunal Dahiya Deepak Saini Anshul Mittal Ankush Shaw Kushal Dave ...	2021/3/8
Optimizing unlicensed coexistence network performance through data learning	Mobile and Ubiquitous Systems: Computing, Networking and Services: 18th EAI International Conference, MobiQuitous 2021, Virtual Event, November 8-11, 2021, Proceedings	Hirozumi Yamaguchi	2022/2/8
Siamesexml: Siamese networks meet extreme classifiers with 100m labels		Kunal Dahiya Ananye Agarwal Deepak Saini K Gururaj Jian Jiao ...	2021/7/1