Monthly Archives: October 2021

To tackle the problem of lexical semantic change, KocLab has developed the first Gaussian word embedding (w2g)-based approach, which has been described in the paper “Semantic Change Detection with Gaussian Word Embeddings” published at IEEE Transactions on Audio, Speech and Language Processing. The proposed method reached high rankings (including the first rank at one of […]

The work of Dr. Koç and his collaborators on sentiment analysis has been published in IEEE Transactions on Neural Networks and Learning Systems. The paper entitled “Multi-Label Sentiment Analysis on 100 Languages with Dynamic Weighting for Label Imbalance” proposes a novel method to overcome the inherent label imbalance problem in multi-label classification by balancing losses […]

The paper entitled “Operator Theory-based Computation of Linear Canonical Transforms” published in Signal Processing by Dr. Koç and his collaborators applied the operator theory to the computation of linear canonical transforms. By exploiting hyperdifferential operators and through a systematic investigation of possible parameters and design choices, the proposed algorithm achieves a discrete linear canonical transform […]