Search Results for author: Yong Liang Goh

Found 5 papers, 2 papers with code

Constrained Layout Generation with Factor Graphs

no code implementations30 Mar 2024 Mohammed Haroon Dupty, Yanfei Dong, Sicong Leng, Guoji Fu, Yong Liang Goh, Wei Lu, Wee Sun Lee

This paper addresses the challenge of object-centric layout generation under spatial constraints, seen in multiple domains including floorplan design process.

Object

Joint Triplet Loss Learning for Next New POI Recommendation

no code implementations25 Sep 2022 Nicholas Lim, Bryan Hooi, See-Kiong Ng, Yong Liang Goh

Sparsity of the User-POI matrix is a well established problem for next POI recommendation, which hinders effective learning of user preferences.

Combining Reinforcement Learning and Optimal Transport for the Traveling Salesman Problem

1 code implementation2 Mar 2022 Yong Liang Goh, Wee Sun Lee, Xavier Bresson, Thomas Laurent, Nicholas Lim

This paper exemplifies the integration of entropic regularized optimal transport techniques as a layer in a deep reinforcement learning network.

Combinatorial Optimization reinforcement-learning +2

Origin-Aware Next Destination Recommendation with Personalized Preference Attention

1 code implementation3 Dec 2020 Nicholas Lim, Bryan Hooi, See-Kiong Ng, Xueou Wang, Yong Liang Goh, Renrong Weng, Rui Tan

Next destination recommendation is an important task in the transportation domain of taxi and ride-hailing services, where users are recommended with personalized destinations given their current origin location.

STP-UDGAT: Spatial-Temporal-Preference User Dimensional Graph Attention Network for Next POI Recommendation

no code implementations6 Oct 2020 Nicholas Lim, Bryan Hooi, See-Kiong Ng, Xueou Wang, Yong Liang Goh, Renrong Weng, Jagannadan Varadarajan

Next Point-of-Interest (POI) recommendation is a longstanding problem across the domains of Location-Based Social Networks (LBSN) and transportation.

Graph Attention

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