activity
20172025
most citedLayered Graph Embedding for Entity Recommendation using Wikipedia in the Yahoo! Knowledge Graph

23 citations · 37 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IR2025

DashCLIP: Leveraging multimodal models for generating semantic embeddings for DoorDash

Omkar Gurjar, Kin Sum Liu, Praveen Kolli +2

Despite the success of vision-language models in various generative tasks, obtaining high-quality semantic representations for products and user intents is still challenging due to…

cs.AI2024

Patrol Security Game: Defending Against Adversary with Freedom in Attack Timing, Location, and Duration

Hao-Tsung Yang, Ting-Kai Weng, Ting-Yu Chang +4

We explored the Patrol Security Game (PSG), a robotic patrolling problem modeled as an extensive-form Stackelberg game, where the attacker determines the timing, location, and dura…

cs.IR2021★ 7 cited

An Analysis Of Entire Space Multi-Task Models For Post-Click Conversion Prediction

Conor O'Brien, Kin Sum Liu, James Neufeld +2

Industrial recommender systems are frequently tasked with approximating probabilities for multiple, often closely related, user actions. For example, predicting if a user will clic…

cs.IR2020★ 23 cited

Layered Graph Embedding for Entity Recommendation using Wikipedia in the Yahoo! Knowledge Graph

Chien-Chun Ni, Kin Sum Liu, Nicolas Torzec

In this paper, we describe an embedding-based entity recommendation framework for Wikipedia that organizes Wikipedia into a collection of graphs layered on top of each other, learn…

cs.LG2019

Topology Based Scalable Graph Kernels

Kin Sum Liu, Chien-Chun Ni, Yu-Yao Lin +1

We propose a new graph kernel for graph classification and comparison using Ollivier Ricci curvature. The Ricci curvature of an edge in a graph describes the connectivity in the lo…

cs.LG2018★ 6 cited

Performing Co-Membership Attacks Against Deep Generative Models

Kin Sum Liu, Chaowei Xiao, Bo Li +1

In this paper we propose a new membership attack method called co-membership attacks against deep generative models including Variational Autoencoders (VAEs) and Generative Adversa…

eess.SY2017★ 1 cited

Data-Driven Robust Control for Type 1 Diabetes Under Meal and Exercise Uncertainties

Nicola Paoletti, Kin Sum Liu, Scott A. Smolka +1

We present a fully closed-loop design for an artificial pancreas (AP) which regulates the delivery of insulin for the control of Type I diabetes. Our AP controller operates in a fu…