activity
20182020
most citedActive Federated Learning

83 citations · 128 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL2020

NUANCED: Natural Utterance Annotation for Nuanced Conversation with Estimated Distributions

Zhiyu Chen, Honglei Liu, Hu Xu +3

Existing conversational systems are mostly agent-centric, which assumes the user utterances would closely follow the system ontology (for NLU or dialogue state tracking). However,…

cs.CL20206 cited

User Memory Reasoning for Conversational Recommendation

Hu Xu, Seungwhan Moon, Honglei Liu +3

We study a conversational recommendation model which dynamically manages users' past (offline) preferences and current (online) requests through a structured and cumulative user me…

cs.LG201983 cited

Active Federated Learning

Jack Goetz, Kshitiz Malik, Duc Bui +3

Federated Learning allows for population level models to be trained without centralizing client data by transmitting the global model to clients, calculating gradients locally, the…

cs.LG201937 cited

Federated User Representation Learning

Duc Bui, Kshitiz Malik, Jack Goetz +4

Collaborative personalization, such as through learned user representations (embeddings), can improve the prediction accuracy of neural-network-based models significantly. We propo…

cs.CL20192 cited

Global Textual Relation Embedding for Relational Understanding

Zhiyu Chen, Hanwen Zha, Honglei Liu +3

Pre-trained embeddings such as word embeddings and sentence embeddings are fundamental tools facilitating a wide range of downstream NLP tasks. In this work, we investigate how to…

cs.LG2018

Explore-Exploit: A Framework for Interactive and Online Learning

Honglei Liu, Anuj Kumar, Wenhai Yang +1

Interactive user interfaces need to continuously evolve based on the interactions that a user has (or does not have) with the system. This may require constant exploration of vario…