Search Results for author:
Found 36 papers, 11 papers with code
HiNet: Novel Multi-Scenario & Multi-Task Learning with Hierarchical Information Extraction
Multi-scenario & multi-task learning has been widely applied to many recommendation systems in industrial applications, wherein an effective and practical approach is to carry out multi-scenario transfer learning on the basis of the Mixture-of-Expert (MoE) architecture.
GATOR: Graph-Aware Transformer with Motion-Disentangled Regression for Human Mesh Recovery from a 2D Pose
3D human mesh recovery from a 2D pose plays an important role in various applications.
Feature Completion Transformer for Occluded Person Re-identification
In this paper, different from most previous works that discard the occluded region, we propose a Feature Completion Transformer (FCFormer) to implicitly complement the semantic information of occluded parts in the feature space.
Diverse Policy Optimization for Structured Action Space
We propose a simple and effective RL method, Diverse Policy Optimization (DPO), to model the policies in structured action space as the energy-based models (EBM) by following the probabilistic RL framework.
HTNet: Human Topology Aware Network for 3D Human Pose Estimation
3D human pose estimation errors would propagate along the human body topology and accumulate at the end joints of limbs.
Ranked #110 on
3D Human Pose Estimation
on Human3.6M
Learning Roles with Emergent Social Value Orientations
Social dilemmas can be considered situations where individual rationality leads to collective irrationality.
Algorithmic Decision-Making Safeguarded by Human Knowledge
In view of such a conflict, we provide a general analytical framework to study the augmentation of algorithmic decisions with human knowledge: the analyst uses the knowledge to set a guardrail by which the algorithmic decision is clipped if the algorithmic output is out of bound, and seems unreasonable.
Evade the Trap of Mediocrity: Promoting Diversity and Novelty in Text Generation via Concentrating Attention
In this work, we dig into the intrinsic mechanism of this problem and found that sparser attention values in Transformer could improve diversity.
Understanding ME? Multimodal Evaluation for Fine-grained Visual Commonsense
Visual commonsense understanding requires Vision Language (VL) models to not only understand image and text but also cross-reference in-between to fully integrate and achieve comprehension of the visual scene described.
Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation
We demonstrate that TRACE could enhance the entanglement of each segment and preceding latent variables and deduce a non-zero lower bound of the KL term, providing a theoretical guarantee of generation diversity.
Fuse It More Deeply! A Variational Transformer with Layer-Wise Latent Variable Inference for Text Generation
The past several years have witnessed Variational Auto-Encoder's superiority in various text generation tasks.
GraphMLP: A Graph MLP-Like Architecture for 3D Human Pose Estimation
To the best of our knowledge, this is the first MLP-Like architecture for 3D human pose estimation in a single frame and a video sequence.
Ranked #45 on
3D Human Pose Estimation
on Human3.6M
StyleBERT: Chinese pretraining by font style information
With the success of down streaming task using English pre-trained language model, the pre-trained Chinese language model is also necessary to get a better performance of Chinese NLP task.
Multi-Agent Path Finding with Prioritized Communication Learning
The learning-based, fully decentralized framework has been introduced to alleviate real-time problems and simultaneously pursue optimal planning policy.
Multi-Agent Path Finding
Multi-agent Reinforcement Learning
+1
CUGE: A Chinese Language Understanding and Generation Evaluation Benchmark
We argue that for general-purpose language intelligence evaluation, the benchmark itself needs to be comprehensive and systematic.
VMAgent: Scheduling Simulator for Reinforcement Learning
A novel simulator called VMAgent is introduced to help RL researchers better explore new methods, especially for virtual machine scheduling.
MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation
Estimating 3D human poses from monocular videos is a challenging task due to depth ambiguity and self-occlusion.
Ranked #8 on
3D Human Pose Estimation
on MPI-INF-3DHP
Interactive Medical Image Segmentation with Self-Adaptive Confidence Calibration
Based on the confidential information, a self-adaptive reward function is designed to provide more detailed feedback, and a simulated label generation mechanism is proposed on unsupervised data to reduce over-reliance on labeled data.
CCPM: A Chinese Classical Poetry Matching Dataset
We hope this dataset can further enhance the study on incorporating deep semantics into the understanding and generation system of Chinese classical poetry.
Weakly-supervised 3D Human Pose Estimation with Cross-view U-shaped Graph Convolutional Network
Instead, exploiting multi-view information is a practical way to achieve absolute 3D human pose estimation.
Monocular 3D Human Pose Estimation
Weakly-supervised 3D Human Pose Estimation
+1
Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation
The modified VTE is termed as Strided Transformer Encoder (STE), which is built upon the outputs of VTE.
Ranked #1 on
3D Human Pose Estimation
on HumanEva-I
Dealing with Non-Stationarity in MARL via Trust-Region Decomposition
In this paper, we introduce a novel notion, the $\delta$-measurement, to explicitly measure the non-stationarity of a policy sequence, which can be further proved to be bounded by the KL-divergence of consecutive joint policies.
Structured Diversification Emergence via Reinforced Organization Control and Hierarchical Consensus Learning
In order to improve the efficiency of cooperation and exploration, we propose a structured diversification emergence MARL framework named {\sc{Rochico}} based on reinforced organization control and hierarchical consensus learning.
Malicious Requests Detection with Improved Bidirectional Long Short-term Memory Neural Networks
Detecting and intercepting malicious requests are one of the most widely used ways against attacks in the network security.
Using Information to Amplify Competition
I characterize the consumer-optimal market segmentation in competitive markets where multiple firms selling differentiated products to consumers with unit demand.
Dimension Reduction in Contextual Online Learning via Nonparametric Variable Selection
Our algorithm achieves the regret $\tilde{O}(T^{(d_x^*+d_y+1)/(d_x^*+d_y+2)})$, where $d_x^*$ is the effective covariate dimension.
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning
Traditional centralized multi-agent reinforcement learning (MARL) algorithms are sometimes unpractical in complicated applications, due to non-interactivity between agents, curse of dimensionality and computation complexity.
Multi-agent Reinforcement Learning
Reinforcement Learning (RL)
+2
MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Space
Though recent neural models make prominent progress in some criteria of poetry quality, generated poems still suffer from the problem of poor diversity.
Learning Structured Communication for Multi-agent Reinforcement Learning
This work explores the large-scale multi-agent communication mechanism under a multi-agent reinforcement learning (MARL) setting.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
HMRL: Hyper-Meta Learning for Sparse Reward Reinforcement Learning Problem
In spite of the success of existing meta reinforcement learning methods, they still have difficulty in learning a meta policy effectively for RL problems with sparse reward.
Iteratively-Refined Interactive 3D Medical Image Segmentation with Multi-Agent Reinforcement Learning
We here propose to model the dynamic process of iterative interactive image segmentation as a Markov decision process (MDP) and solve it with reinforcement learning (RL).
A Dimension-free Algorithm for Contextual Continuum-armed Bandits
The literature has shown that for Lipschitz-continuous functions, the optimal regret is $\tilde{O}(T^{\frac{d_x+d_y+1}{d_x+d_y+2}})$, where $d_x$ and $d_y$ are the dimensions of contexts and arms, and thus suffers from the curse of dimensionality.
Jiuge: A Human-Machine Collaborative Chinese Classical Poetry Generation System
By exposing the options of poetry genres, styles and revision modes, Jiuge, acting as a professional assistant, allows constant and active participation of users in poetic creation.
Stylistic Chinese Poetry Generation via Unsupervised Style Disentanglement
The ability to write diverse poems in different styles under the same poetic imagery is an important characteristic of human poetry writing.
Automatic Poetry Generation with Mutual Reinforcement Learning
Human experts evaluate poetry in terms of some specific criteria, instead of word-level likelihood.
