Search Results for author: Anil Ramakrishna

Found 8 papers, 1 papers with code

FedMultimodal: A Benchmark For Multimodal Federated Learning

no code implementations15 Jun 2023 Tiantian Feng, Digbalay Bose, Tuo Zhang, Rajat Hebbar, Anil Ramakrishna, Rahul Gupta, Mi Zhang, Salman Avestimehr, Shrikanth Narayanan

In order to facilitate the research in multimodal FL, we introduce FedMultimodal, the first FL benchmark for multimodal learning covering five representative multimodal applications from ten commonly used datasets with a total of eight unique modalities.

Emotion Recognition Federated Learning

Federated Learning with Noisy User Feedback

no code implementations NAACL 2022 Rahul Sharma, Anil Ramakrishna, Ansel MacLaughlin, Anna Rumshisky, Jimit Majmudar, Clement Chung, Salman Avestimehr, Rahul Gupta

Federated learning (FL) has recently emerged as a method for training ML models on edge devices using sensitive user data and is seen as a way to mitigate concerns over data privacy.

Federated Learning text-classification +1

Towards Realistic Single-Task Continuous Learning Research for NER

1 code implementation Findings (EMNLP) 2021 Justin Payan, Yuval Merhav, He Xie, Satyapriya Krishna, Anil Ramakrishna, Mukund Sridhar, Rahul Gupta

There is an increasing interest in continuous learning (CL), as data privacy is becoming a priority for real-world machine learning applications.


Joint Multi-Dimensional Model for Global and Time-Series Annotations

no code implementations6 May 2020 Anil Ramakrishna, Rahul Gupta, Shrikanth Narayanan

In this work we address this by proposing a generative model for multi-dimensional annotation fusion, which models the dimensions jointly leading to more accurate ground truth estimates.

Time Series Time Series Analysis

Linguistic analysis of differences in portrayal of movie characters

no code implementations ACL 2017 Anil Ramakrishna, Victor R. Mart{\'\i}nez, Mal, Nikolaos rakis, Karan Singla, Shrikanth Narayanan

We examine differences in portrayal of characters in movies using psycholinguistic and graph theoretic measures computed directly from screenplays.


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