223 citations · 409 across the 18 of their papers we have counts for
6 papers · 1 filter
Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation
Yogesh Balaji, Rama Chellappa, Soheil Feizi
Optimal Transport (OT) distances such as Wasserstein have been used in several areas such as GANs and domain adaptation. OT, however, is very sensitive to outliers (samples with la…
The Effectiveness of Memory Replay in Large Scale Continual Learning
Yogesh Balaji, Mehrdad Farajtabar, Dong Yin +2
We study continual learning in the large scale setting where tasks in the input sequence are not limited to classification, and the outputs can be of high dimension. Among multiple…
Winning Lottery Tickets in Deep Generative Models
Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi
The lottery ticket hypothesis suggests that sparse, sub-networks of a given neural network, if initialized properly, can be trained to reach comparable or even better performance t…
Learning to Balance Specificity and Invariance for In and Out of Domain Generalization
Prithvijit Chattopadhyay, Yogesh Balaji, Judy Hoffman
We introduce Domain-specific Masks for Generalization, a model for improving both in-domain and out-of-domain generalization performance. For domain generalization, the goal is to…
Curriculum Manager for Source Selection in Multi-Source Domain Adaptation
Luyu Yang, Yogesh Balaji, Ser-Nam Lim +1
The performance of Multi-Source Unsupervised Domain Adaptation depends significantly on the effectiveness of transfer from labeled source domain samples. In this paper, we proposed…
Unsupervised Anomaly Detection with Adversarial Mirrored AutoEncoders
Gowthami Somepalli, Yexin Wu, Yogesh Balaji +2
Detecting out of distribution (OOD) samples is of paramount importance in all Machine Learning applications. Deep generative modeling has emerged as a dominant paradigm to model co…