1 citations · 1 across the 7 of their papers we have counts for
7 papers
Two Dimensions Govern Agnostic Multiclass Transductive Learning
Pahan Dewasurendra
In transductive classification, an adversary fixes a labeled population, one label is hidden uniformly, and the learner sees all remaining labels. For binary classes, agnostic tran…
Self-Bounding Regret Matching+ in Potential Games and Product-Simplex Optimization
Pahan Dewasurendra, Subhashini Jayawardhana
Regret matching+ (RM+) is parameter free, scale invariant, and central to large game solving, but its only general individual-regret guarantee grows as . A recent ICLR re…
Convex Networks Remain Hard to Certify: Dimension-Accuracy Barriers for Lipschitz Constants
Pahan Dewasurendra, Subhashini Jayawardhana
Input-convex neural networks permit globally tractable minimization over their inputs, so one might expect their global regularity to be tractable in low input dimension. We prove…
Multiscale Reward Hedging from Correct Demonstrations
Pahan Dewasurendra
Learning from correct demonstrations is harder than supervised learning when many answers are correct: after predicting, the learner sees one valid answer but not whether its own a…
Dirichlet Follow-the-Leader Closes the Gap in Simultaneous Multiclass U-Calibration
Pahan Dewasurendra
Can one forecaster attain the optimal regret rate for every bounded proper loss and also adapt to every smooth proper loss? Recent work answered this up to a dimension gap. Its sel…
Unsupervised Replay Strategies for Continual Learning with Limited Data
Anthony Bazhenov, Pahan Dewasurendra, Giri P. Krishnan +1
Artificial neural networks (ANNs) show limited performance with scarce or imbalanced training data and face challenges with continuous learning, such as forgetting previously learn…
Sleep-Like Unsupervised Replay Improves Performance when Data are Limited or Unbalanced
Anthony Bazhenov, Pahan Dewasurendra, Giri Krishnan +1
The performance of artificial neural networks (ANNs) degrades when training data are limited or imbalanced. In contrast, the human brain can learn quickly from just a few examples.…