Vedant Nanda

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 29

Top Topics

Bipartite Matching

Profit Maximizing

Top Venues

Publications

Till Speicher, Mohammad Aflah Khan, Qinyuan Wu, Vedant Nanda, Soumi Das, Bishwamittra Ghosh, Krishna P. Gummadi, Evimaria Terzi
Understanding Memorisation in LLMs: Dynamics, Influencing Factors, and Implications. CoRR (2024)
Till Speicher, Vedant Nanda, Krishna P. Gummadi
Understanding the Role of Invariance in Transfer Learning. CoRR (2024)
Qinyuan Wu, Mohammad Aflah Khan, Soumi Das, Vedant Nanda, Bishwamittra Ghosh, Camila Kolling, Till Speicher, Laurent Bindschaedler, Krishna P. Gummadi, Evimaria Terzi
Towards Reliable Latent Knowledge Estimation in LLMs: In-Context Learning vs. Prompting Based Factual Knowledge Extraction. CoRR (2024)
Ricardo Dominguez-Olmedo, Vedant Nanda, Rediet Abebe, Stefan Bechtold, Christoph Engel, Jens Frankenreiter, Krishna P. Gummadi, Moritz Hardt, Michael Livermore
Lawma: The Power of Specialization for Legal Tasks. CoRR (2024)
Till Speicher, Vedant Nanda, Krishna P. Gummadi
Understanding the Role of Invariance in Transfer Learning. Trans. Mach. Learn. Res. 2024 (2024)
Camila Kolling, Till Speicher, Vedant Nanda, Mariya Toneva, Krishna P. Gummadi
Pointwise Representational Similarity. CoRR (2023)
Vedant Nanda, Ayan Majumdar, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Bradley C. Love, Adrian Weller
Do Invariances in Deep Neural Networks Align with Human Perception? AAAI (2023)
Gabriele Merlin, Vedant Nanda, Ruchit Rawal, Mariya Toneva
What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation. CoLLAs (2023)
Gabriele Merlin, Vedant Nanda, Ruchit Rawal, Mariya Toneva
What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation. CoRR (2023)
Vedant Nanda, Till Speicher, John P. Dickerson, Soheil Feizi, Krishna P. Gummadi, Adrian Weller
Diffused Redundancy in Pre-trained Representations. CoRR (2023)
Seyed A. Esmaeili, Sharmila Duppala, Davidson Cheng, Vedant Nanda, Aravind Srinivasan, John P. Dickerson
Rawlsian Fairness in Online Bipartite Matching: Two-Sided, Group, and Individual. AAAI (2023)
Vedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Soheil Feizi, Adrian Weller
Diffused Redundancy in Pre-trained Representations. NeurIPS (2023)
Seyed A. Esmaeili, Sharmila Duppala, Vedant Nanda, Aravind Srinivasan, John P. Dickerson
Rawlsian Fairness in Online Bipartite Matching: Two-sided, Group, and Individual. CoRR (2022)
Vedant Nanda, Till Speicher, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Adrian Weller
Measuring Representational Robustness of Neural Networks Through Shared Invariances. CoRR (2022)
Seyed A. Esmaeili, Sharmila Duppala, Vedant Nanda, Aravind Srinivasan, John P. Dickerson
Rawlsian Fairness in Online Bipartite Matching: Two-sided, Group, and Individual. AAMAS (2022)
Vedant Nanda, Till Speicher, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Adrian Weller
Measuring Representational Robustness of Neural Networks Through Shared Invariances. ICML (2022)
Vedant Nanda, Ayan Majumdar, Camila Kolling, John P. Dickerson, Krishna P. Gummadi, Bradley C. Love, Adrian Weller
Exploring Alignment of Representations with Human Perception. CoRR (2021)
Vedant Nanda, Samuel Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson
Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. FAccT (2021)
Valeriia Cherepanova, Vedant Nanda, Micah Goldblum, John P. Dickerson, Tom Goldstein
Technical Challenges for Training Fair Neural Networks. CoRR (2021)
Vedant Nanda, Samuel Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson
Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning. CoRR (2020)
Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan
Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours. AAAI (2020)
Vedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Muhammad Bilal Zafar
Unifying Model Explainability and Robustness via Machine-Checkable Concepts. CoRR (2020)
Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan
Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours. AIES (2020)
Vedant Nanda, Pan Xu, Karthik Abinav Sankararaman, John P. Dickerson, Aravind Srinivasan
Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms During High-Demand Hours. CoRR (2019)
Hoda Heidari, Vedant Nanda, Krishna P. Gummadi
On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning. CoRR (2019)
Hoda Heidari, Vedant Nanda, Krishna P. Gummadi
On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning. ICML (2019)
Vedant Nanda, Hemank Lamba, Divyansh Agarwal, Megha Arora, Niharika Sachdeva, Ponnurangam Kumaraguru
Stop the KillFies! Using Deep Learning Models to Identify Dangerous Selfies. WWW (Companion Volume) (2018)
Siddharth Singh, Vedant Nanda, Rijurekha Sen, Satadal Sengupta, Ponnurangam Kumaraguru, Krishna P. Gummadi
Leveraging Facebook's Free Basics Engine for Web Service Deployment in Developing Regions. ICTD (2017)
Siddharth Singh, Vedant Nanda, Rijurekha Sen, Sohaib Ahmad, Satadal Sengupta, Amreesh Phokeer, Zaid Ahmed Farooq, Taslim Arefin Khan, Ponnurangam Kumaraguru, Ihsan Ayyub Qazi, David R. Choffnes, Krishna P. Gummadi
An Empirical Analysis of Facebook's Free Basics. SIGMETRICS (Abstracts) (2017)