Search Results for author:
Found 10 papers, 2 papers with code
Topic-switch adapted Japanese Dialogue System based on PLATO-2
Furthermore, our proposed topic-switch algorithm achieves an average score of 1. 767 and outperforms PLATO-JDS by 0. 267, indicating its effectiveness in improving the user experience of our system.
Do I Have Your Attention: A Large Scale Engagement Prediction Dataset and Baselines
To this end, a large scale multi-faceted engagement in the wild dataset is proposed.
Complete Cross-triplet Loss in Label Space for Audio-visual Cross-modal Retrieval
In this paper, to reduce the interference of hard negative samples in representation learning, we propose a new AV-CMR model to optimize semantic features by directly predicting labels and then measuring the intrinsic correlation between audio-visual data using complete cross-triple loss.
VQA-GNN: Reasoning with Multimodal Semantic Graph for Visual Question Answering
In this work, we propose a novel visual question answering method, VQA-GNN, which unifies the image-level information and conceptual knowledge to perform joint reasoning of the scene.
Cloning Outfits from Real-World Images to 3D Characters for Generalizable Person Re-Identification
To address this, in this work, an automatic approach is proposed to directly clone the whole outfits from real-world person images to virtual 3D characters, such that any virtual person thus created will appear very similar to its real-world counterpart.
Ranked #1 on
Unsupervised Domain Adaptation
on ClonedPerson
(using extra training data)
Generalizable Person Re-identification
Unsupervised Domain Adaptation
+1
Sequential Search with Off-Policy Reinforcement Learning
Recent years have seen a significant amount of interests in Sequential Recommendation (SR), which aims to understand and model the sequential user behaviors and the interactions between users and items over time.
Hypothesis Testing for Unknown Dynamical Systems and System Anomaly Detection via Autoencoders
We study the hypothesis testing problem for unknown dynamical systems.
Offline Meta-level Model-based Reinforcement Learning Approach for Cold-Start Recommendation
To improve adaptation efficiency, we learn to recover the user policy and reward from only a few interactions via an inverse reinforcement learning method to assist a meta-level recommendation agent.
Model-based Reinforcement Learning
Recommendation Systems
+2
Surpassing Real-World Source Training Data: Random 3D Characters for Generalizable Person Re-Identification
To address this, we propose to automatically synthesize a large-scale person re-identification dataset following a set-up similar to real surveillance but with virtual environments, and then use the synthesized person images to train a generalizable person re-identification model.
Domain Generalization
Generalizable Person Re-identification
+1
STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control
Moreover, based on the temporally-dependent traffic information, we design a Graph Neural Network based model to represent relationships among multiple traffic lights, and the decision for each traffic light will be made in a distributed way by the deep Q-learning method.
