I am a M.Sc student at the RLAI lab working with Dr. Martha White on learning representations from raw sensory data that are conducive for planning, quick adaptation, and continual learning. Previously, I worked at TUKL-SEECS with Dr. Faisal Shafait on various Computer Vision and Machine Learning R&D projects during most of my undergraduate. I also represented my country, Pakistan, at 55th International Mathematical Olympiad , and XXVI Asian Pacific Mathematical Olympiad before college, receiving an honorable-mention and a bronze medal respectively.
We propose OML, an objective for learning representations by using catastrophic interference as a training
signal. Resultant representations are naturally sparse, accelerate future learning and are robust to forgetting
under online updates in continual learning.
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We isolate the truly effective existing ideas for incremental classifier learning from those that only work under certain conditions. Moreover, we propose a dynamic threshold moving algorithm that can successfully remove bias from an incrementally learned classifier when learning by knowledge distillation.
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We propose a computationally efficient document segmentation algorithm that recursively uses
convolutional neural networks to precisely
localize a document in a natural image in real-time.
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