Search Results for author: Jun Song

Found 16 papers, 7 papers with code

GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation

1 code implementation17 Jun 2024 Shihao Cai, Keqin Bao, Hangyu Guo, Jizhi Zhang, Jun Song, Bo Zheng

To overcome this issue, we introduce a novel pipeline that leverages GPT-4 and GPT-4V to generate relatively basic geometry problems with aligned text and images, facilitating model learning.

Image Generation Math

Enhancing Sufficient Dimension Reduction via Hellinger Correlation

1 code implementation30 May 2024 Seungbeom Hong, Ilmun Kim, Jun Song

In this work, we develop a new theory and method for sufficient dimension reduction (SDR) in single-index models, where SDR is a sub-field of supervised dimension reduction based on conditional independence.

Dimensionality Reduction

Demystify Mamba in Vision: A Linear Attention Perspective

1 code implementation26 May 2024 Dongchen Han, Ziyi Wang, Zhuofan Xia, Yizeng Han, Yifan Pu, Chunjiang Ge, Jun Song, Shiji Song, Bo Zheng, Gao Huang

By exploring the similarities and disparities between the effective Mamba and subpar linear attention Transformer, we provide comprehensive analyses to demystify the key factors behind Mamba's success.

Image Classification

Dreamer XL: Towards High-Resolution Text-to-3D Generation via Trajectory Score Matching

1 code implementation18 May 2024 Xingyu Miao, Haoran Duan, Varun Ojha, Jun Song, Tejal Shah, Yang Long, Rajiv Ranjan

In this work, we propose a novel Trajectory Score Matching (TSM) method that aims to solve the pseudo ground truth inconsistency problem caused by the accumulated error in Interval Score Matching (ISM) when using the Denoising Diffusion Implicit Models (DDIM) inversion process.

3D Generation Denoising +1

Semantic segmentation of SEM images of lower bainitic and tempered martensitic steels

no code implementations2 Dec 2023 Xiaohan Bie, Manoj Arthanari, Evelin Barbosa de Melo, Juancheng Li, Stephen Yue, Salim Brahimi, Jun Song

Our findings reveal that lower bainite and tempered martensite exhibit comparable volume percentages of carbides, albeit with a more uniform distribution of carbides in tempered martensite.

Semantic Segmentation

Provably Convergent Policy Optimization via Metric-aware Trust Region Methods

no code implementations25 Jun 2023 Jun Song, Niao He, Lijun Ding, Chaoyue Zhao

Trust-region methods based on Kullback-Leibler divergence are pervasively used to stabilize policy optimization in reinforcement learning.

Continuous Control Policy Gradient Methods

Towards Optimal Pricing of Demand Response -- A Nonparametric Constrained Policy Optimization Approach

no code implementations24 Jun 2023 Jun Song, Chaoyue Zhao

Demand response (DR) has been demonstrated to be an effective method for reducing peak load and mitigating uncertainties on both the supply and demand sides of the electricity market.

Reinforcement Learning (RL)

Decision-Dependent Distributionally Robust Markov Decision Process Method in Dynamic Epidemic Control

no code implementations24 Jun 2023 Jun Song, William Yang, Chaoyue Zhao

In this paper, we present a Distributionally Robust Markov Decision Process (DRMDP) approach for addressing the dynamic epidemic control problem.

Efficient Wasserstein and Sinkhorn Policy Optimization

no code implementations29 Sep 2021 Jun Song, Chaoyue Zhao, Niao He

Trust-region methods based on Kullback-Leibler divergence are pervasively used to stabilize policy optimization in reinforcement learning.

Policy Gradient Methods Reinforcement Learning (RL)

Multivariate functional group sparse regression: functional predictor selection

2 code implementations5 Jul 2021 Ali Mahzarnia, Jun Song

In this paper, we propose methods for functional predictor selection and the estimation of smooth functional coefficients simultaneously in a scalar-on-function regression problem under high-dimensional multivariate functional data setting.


Optimistic Distributionally Robust Policy Optimization

1 code implementation14 Jun 2020 Jun Song, Chaoyue Zhao

Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO), as the widely employed policy based reinforcement learning (RL) methods, are prone to converge to a sub-optimal solution as they limit the policy representation to a particular parametric distribution class.

reinforcement-learning Reinforcement Learning (RL)

Deep-MAPS: Machine Learning based Mobile Air Pollution Sensing

no code implementations28 Apr 2019 Jun Song, Ke Han

Mobile and ubiquitous sensing of urban air quality has received increased attention as an economically and operationally viable means to survey atmospheric environment with high spatial-temporal resolution.

BIG-bench Machine Learning Management

Parallel Chromatic MCMC with Spatial Partitioning

no code implementations2 Dec 2016 Jun Song, David A. Moore

We introduce a novel approach for parallelizing MCMC inference in models with spatially determined conditional independence relationships, for which existing techniques exploiting graphical model structure are not applicable.

Event Detection

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