Search Results for author: Bo Tang

Found 11 papers, 1 papers with code

Interpretable performance analysis towards offline reinforcement learning: A dataset perspective

no code implementations12 May 2021 Chenyang Xi, Bo Tang, Jiajun Shen, Xinfu Liu, Feiyu Xiong, Xueying Li

We make it open-source for fair and comprehensive competitions between offline RL algorithms with complete datasets and checkpoints being provided.

Offline RL Q-Learning

Constrained Radar Waveform Design for Range Profiling

no code implementations18 Mar 2021 Bo Tang, Jun Liu, Hai Wang, Yihua Hu

Range profiling refers to the measurement of target response along the radar slant range.

Stragglers Are Not Disaster: A Hybrid Federated Learning Algorithm with Delayed Gradients

no code implementations12 Feb 2021 Xingyu Li, Zhe Qu, Bo Tang, Zhuo Lu

Federated learning (FL) is a new machine learning framework which trains a joint model across a large amount of decentralized computing devices.

Federated Learning

Overcoming Long-term Catastrophic Forgetting through Adversarial Neural Pruning and Synaptic Consolidation

1 code implementation19 Dec 2019 Jian Peng, Bo Tang, Hao Jiang, Zhuo Li, Yinjie Lei, Tao Lin, Haifeng Li

It is due to two facts: first, as the model learns more tasks, the intersection of the low-error parameter subspace satisfying for these tasks becomes smaller or even does not exist; second, when the model learns a new task, the cumulative error keeps increasing as the model tries to protect the parameter configuration of previous tasks from interference.

Image Classification

Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?

no code implementations13 Dec 2018 Mingyue Shang, Zhenxin Fu, Hongzhi Yin, Bo Tang, Dongyan Zhao, Rui Yan

In this paper, we incorporate the logic information with the help of the Natural Language Inference (NLI) task to the Story Cloze Test (SCT).

Cloze Test Natural Language Inference +1

On the Recursive Teaching Dimension of VC Classes

no code implementations NeurIPS 2016 Xi Chen, Yu Cheng, Bo Tang

This is the first upper bound for $RTD(C)$ that depends only on $VCD(C)$, independent of the size of the concept class $|C|$ and its~domain size $n$.

A Local Density-Based Approach for Local Outlier Detection

no code implementations28 Jun 2016 Bo Tang, Haibo He

A Relative Density-based Outlier Score (RDOS) is introduced to measure the local outlierness of objects, in which the density distribution at the location of an object is estimated with a local KDE method based on extended nearest neighbors of the object.

Density Estimation Outlier Detection

Kernel-based Generative Learning in Distortion Feature Space

no code implementations21 Jun 2016 Bo Tang, Paul M. Baggenstoss, Haibo He

The recognition diversity indicates that a hybrid combination of the proposed generative classifier and the discriminative classifier could further improve the classification performance.

Classification General Classification

FSMJ: Feature Selection with Maximum Jensen-Shannon Divergence for Text Categorization

no code implementations20 Jun 2016 Bo Tang, Haibo He

In this paper, we present a new wrapper feature selection approach based on Jensen-Shannon (JS) divergence, termed feature selection with maximum JS-divergence (FSMJ), for text categorization.

Feature Selection Text Categorization

EEF: Exponentially Embedded Families with Class-Specific Features for Classification

no code implementations11 May 2016 Bo Tang, Steven Kay, Haibo He, Paul M. Baggenstoss

In this letter, we present a novel exponentially embedded families (EEF) based classification method, in which the probability density function (PDF) on raw data is estimated from the PDF on features.

Classification Feature Selection +2

Toward Optimal Feature Selection in Naive Bayes for Text Categorization

no code implementations9 Feb 2016 Bo Tang, Steven Kay, Haibo He

Based on the JMH-divergence, we develop two efficient feature selection methods, termed maximum discrimination ($MD$) and $MD-\chi^2$ methods, for text categorization.

Feature Selection General Classification +2

Cannot find the paper you are looking for? You can Submit a new open access paper.