9 citations · 21 across the 9 of their papers we have counts for
5 papers · 1 filter
Towards a Hypothesis on Visual Transformation based Self-Supervision
Dipan K. Pal, Sreena Nallamothu, Marios Savvides
We propose the first qualitative hypothesis characterizing the behavior of visual transformation based self-supervision, called the VTSS hypothesis. Given a dataset upon which a se…
Learning Non-Parametric Invariances from Data with Permanent Random Connectomes
Dipan K. Pal, Akshay Chawla, Marios Savvides
One of the fundamental problems in supervised classification and in machine learning in general, is the modelling of non-parametric invariances that exist in data. Most prior art h…
Max-Margin Invariant Features from Transformed Unlabeled Data
Dipan K. Pal, Ashwin A. Kannan, Gautam Arakalgud +1
The study of representations invariant to common transformations of the data is important to learning. Most techniques have focused on local approximate invariance implemented with…
Emergence of Selective Invariance in Hierarchical Feed Forward Networks
Dipan K. Pal, Vishnu Boddeti, Marios Savvides
Many theories have emerged which investigate how in- variance is generated in hierarchical networks through sim- ple schemes such as max and mean pooling. The restriction to max/me…
Unitary-Group Invariant Kernels and Features from Transformed Unlabeled Data
Dipan K. Pal, Marios Savvides
The study of representations invariant to common transformations of the data is important to learning. Most techniques have focused on local approximate invariance implemented with…