116 citations · 139 across the 15 of their papers we have counts for
4 papers · 1 filter
UniMLR: Modeling Implicit Class Significance for Multi-Label Ranking
V. Bugra Yesilkaynak, Emine Dari, Alican Mertan +1
Existing multi-label ranking (MLR) frameworks only exploit information deduced from the bipartition of labels into positive and negative sets. Therefore, they do not benefit from r…
Morphological Cognition: Classifying MNIST Digits Through Morphological Computation Alone
Alican Mertan, Nick Cheney
With the rise of modern deep learning, neural networks have become an essential part of virtually every artificial intelligence system, making it difficult even to imagine differen…
Evolutionary Brain-Body Co-Optimization Consistently Fails to Select for Morphological Potential
Alican Mertan, Nick Cheney
Brain-body co-optimization remains a challenging problem. To understand and overcome its challenges, we exhaustively map a morphology-fitness landscape: we train controllers for ea…
Controller Distillation Reduces Fragile Brain-Body Co-Adaptation and Enables Migrations in MAP-Elites
Alican Mertan, Nick Cheney
Brain-body co-optimization suffers from fragile co-adaptation where brains become over-specialized for particular bodies, hindering their ability to transfer well to others. Evolut…