9 citations · 14 across the 7 of their papers we have counts for
7 papers
Perturbing the Gradient for Alleviating Meta Overfitting
Manas Gogoi, Sambhavi Tiwari, Shekhar Verma
The reason for Meta Overfitting can be attributed to two factors: Mutual Non-exclusivity and the Lack of diversity, consequent to which a single global function can fit the support…
FAM: fast adaptive federated meta-learning
Indrajeet Kumar Sinha, Shekhar Verma, Krishna Pratap Singh
In this work, we propose a fast adaptive federated meta-learning (FAM) framework for collaboratively learning a single global model, which can then be personalized locally on indiv…
Deep Learning Techniques in Extreme Weather Events: A Review
Shikha Verma, Kuldeep Srivastava, Akhilesh Tiwari +1
Extreme weather events pose significant challenges, thereby demanding techniques for accurate analysis and precise forecasting to mitigate its impact. In recent years, deep learnin…
Learning to Learn with Indispensable Connections
Sambhavi Tiwari, Manas Gogoi, Shekhar Verma +1
Meta-learning aims to solve unseen tasks with few labelled instances. Nevertheless, despite its effectiveness for quick learning in existing optimization-based methods, it has seve…
Hybrid Model using Feature Extraction and Non-linear SVM for Brain Tumor Classification
Lalita Mishra, Shekhar Verma, Shirshu Varma
It is essential to classify brain tumors from magnetic resonance imaging (MRI) accurately for better and timely treatment of the patients. In this paper, we propose a hybrid model,…
Adaptive Prototypical Networks
Manas Gogoi, Sambhavi Tiwari, Shekhar Verma
Prototypical network for Few shot learning tries to learn an embedding function in the encoder that embeds images with similar features close to one another in the embedding space.…