6 papers
Sharp Concentration Bounds for Bundle-Valued Statistics on Manifolds
Swagatam Das, Vaclav Snasel
Many geometric statistics and manifold learning pipelines routinely produce observations -- such as tangent vectors or local frames -- whose natural home is a varying family of fib…
Rebalancing with Calibrated Sub-classes (RCS): A Statistical Fusion-based Framework for Robust Imbalanced Classification across Modalities
Priyobrata Mondal, Faizanuddin Ansari, Swagatam Das
Class imbalance, where certain classes have insufficient data, poses a critical challenge for robust classification, often biasing models toward majority classes. Distribution cali…
APFEx: Adaptive Pareto Front Explorer for Intersectional Fairness
Priyobrata Mondal, Faizanuddin Ansari, Swagatam Das
Ensuring fairness in machine learning models is critical, especially when biases compound across intersecting protected attributes like race, gender, and age. While existing method…
Assessing the Limits of In-Context Learning beyond Functions using Partially Ordered Relation
Debanjan Dutta, Faizanuddin Ansari, Swagatam Das
Generating rational and generally accurate responses to tasks, often accompanied by example demonstrations, highlights Large Language Model's (LLM's) remarkable In-Context Learning…
Generative Adversarial Network based Voice Conversion: Techniques, Challenges, and Recent Advancements
Sandipan Dhar, Nanda Dulal Jana, Swagatam Das
Voice conversion (VC) stands as a crucial research area in speech synthesis, enabling the transformation of a speaker's vocal characteristics to resemble another while preserving t…
Collective Learning Mechanism based Optimal Transport Generative Adversarial Network for Non-parallel Voice Conversion
Sandipan Dhar, Md. Tousin Akhter, Nanda Dulal Jana +1
After demonstrating significant success in image synthesis, Generative Adversarial Network (GAN) models have likewise made significant progress in the field of speech synthesis, le…