Here we post information on topics and awards, including the latest news about Ueda Research Laboratory.
Two of our papers, "Baxter permutation process" and "Meta-learning from Tasks with Heterogeneous Attribute Spaces," were accepted by NeurIPS2020.
Our paper, "Time-delayed collective flow diffusion models for inferring latent people flow from aggregated data at limited locations," was accepted by Artificial Intelligence.
Our paper, "Gamifying World Wide Web Using Web Browsers," was selected Spacially Selected Paper by Information Processing Society of Japan.
Our paper, "Reinforcement Learning in Latent Action Sequence Space," was accepted by IROS2020.
Our paper, "Probabilistic Pedestrian Models for Estimating Unobserved Road Populations," was accepted by IEEE TITS.
Our paper, "Efficient algorithm for the b-matching graphICDM," was accepted by SIGKDD2020.
Our paper, "Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance," was accepted by ICML2020.
Our paper, "Frame-Level Phoneme-Invariant Speaker Embedding for Text-Independent Speaker Recognition on Extremely Short Utterances," was accepted by ICASSP2020.
Our paper, "Regional garbage amount estimation by vehicle activity recognition using motion sensors mounted on garbage collecting trucks and analysis of regional characteristics," was selected Best paper award of IPSJ SIG on UBI.
Two of our papers, "Semi-supervised Learning for Maximizing the Partial AUC" and "Co-occurrence Estimation from Aggregated Data with Auxiliary Information," were accepted by AAAI2020.
Our paper, “Read the Silence: Well-timed Recommendation via Admixture Marked Point Process,” was accepted by AAAI-17 (AAAI Conference on Artificial Intelligence).
Our paper, “A Semi-supervised AUC Optimization Method with Generative Models,” was accepted by ICDM2016 (IEEE International Conference on Data Mining).
Two of our papers, “Higher-Order Factorization Machines” and “Multi-view anomaly detection via robust probabilistic latent variable models,” were accepted by NIPS2016 (Neural Information Processing Systems).
The fellow, Dr. Ueda, received an Achievement Reward from the Institute of Electronics, Information and Communication Engineers for "Pioneering Study on Statistical Machine Learning."
Our paper, “Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms,” was published in ICML2016 (International Conference on Machine Learning).
Ueda Research Laboratory was established.