Search Results for author: Steven C. H. Hoi

Found 85 papers, 41 papers with code

Activity Regularization for Continual Learning

no code implementations ICLR 2019 Quang H. Pham, Steven C. H. Hoi

While deep neural networks have achieved remarkable successes, they suffer the well-known catastrophic forgetting issue when switching from existing tasks to tackle a new one.

Continual Learning Multi-Task Learning

Paired Cross-Modal Data Augmentation for Fine-Grained Image-to-Text Retrieval

no code implementations29 Jul 2022 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

When we do online paired data augmentation, we first generate augmented text through random token replacement, then pass the augmented text into the latent space alignment module to output the latent codes, which are finally fed to StyleGAN2 to generate the augmented images.

Cross-Modal Retrieval Data Augmentation +1

3D Cartoon Face Generation with Controllable Expressions from a Single GAN Image

no code implementations29 Jul 2022 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

To this end, we discover the semantic meanings of StyleGAN latent space, such that we are able to produce face images of various expressions, poses, and lighting by controlling the latent codes.

Face Generation Face Model

CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning

2 code implementations5 Jul 2022 Hung Le, Yue Wang, Akhilesh Deepak Gotmare, Silvio Savarese, Steven C. H. Hoi

To address the limitations, we propose "CodeRL", a new framework for program synthesis tasks through pretrained LMs and deep reinforcement learning (RL).

Code Generation Pretrained Language Models +2

Causality-Based Multivariate Time Series Anomaly Detection

no code implementations30 Jun 2022 Wenzhuo Yang, Kun Zhang, Steven C. H. Hoi

Anomaly detection in multivariate time series plays an important role in monitoring the behaviors of various real-world systems, e. g., IT system operations or manufacturing industry.

Anomaly Detection Time Series Anomaly Detection

Multimodal Dialogue State Tracking

1 code implementation NAACL 2022 Hung Le, Nancy F. Chen, Steven C. H. Hoi

Specifically, we introduce a novel dialogue state tracking task to track the information of visual objects that are mentioned in video-grounded dialogues.

Dialogue State Tracking Video Understanding

Masked Unsupervised Self-training for Zero-shot Image Classification

1 code implementation7 Jun 2022 Junnan Li, Silvio Savarese, Steven C. H. Hoi

We demonstrate the efficacy of MUST on 8 downstream tasks across a variety of domains, where it improves upon CLIP by a large margin and narrows the performance gap between unsupervised and supervised classification.

Classification Image Classification +2

OmniXAI: A Library for Explainable AI

1 code implementation1 Jun 2022 Wenzhuo Yang, Hung Le, Silvio Savarese, Steven C. H. Hoi

We introduce OmniXAI (short for Omni eXplainable AI), an open-source Python library of eXplainable AI (XAI), which offers omni-way explainable AI capabilities and various interpretable machine learning techniques to address the pain points of understanding and interpreting the decisions made by machine learning (ML) in practice.

Counterfactual Explanation Decision Making +3

Vector-Quantized Input-Contextualized Soft Prompts for Natural Language Understanding

no code implementations23 May 2022 Rishabh Bhardwaj, Amrita Saha, Steven C. H. Hoi

Prompt Tuning (PT) has been largely successful as a parameter-efficient way of conditioning large-scale pre-trained language models towards a downstream task.

Natural Language Understanding NER +2

Mining Root Cause Knowledge from Cloud Service Incident Investigations for AIOps

no code implementations21 Apr 2022 Amrita Saha, Steven C. H. Hoi

ICA forms the backbone of a simple-yet-effective Retrieval based RCA for new incidents, through an Information Retrieval system to search and rank past incidents and detect likely root causes from them, given the incident symptom.

Information Retrieval Management

Learning Fast and Slow for Online Time Series Forecasting

no code implementations23 Feb 2022 Quang Pham, Chenghao Liu, Doyen Sahoo, Steven C. H. Hoi

The fast adaptation capability of deep neural networks in non-stationary environments is critical for online time series forecasting.

Time Series Forecasting

Align and Prompt: Video-and-Language Pre-training with Entity Prompts

1 code implementation CVPR 2022 Dongxu Li, Junnan Li, Hongdong Li, Juan Carlos Niebles, Steven C. H. Hoi

To achieve this, we first introduce an entity prompter module, which is trained with VTC to produce the similarity between a video crop and text prompts instantiated with entity names.

Ranked #2 on Visual Question Answering on MSRVTT-QA (using extra training data)

Entity Alignment Video Retrieval +1

Node-wise Localization of Graph Neural Networks

no code implementations27 Oct 2021 Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi

Ideally, how a node receives its neighborhood information should be a function of its local context, to diverge from the global GNN model shared by all nodes.

Representation Learning

Improving Tail-Class Representation with Centroid Contrastive Learning

no code implementations19 Oct 2021 Anthony Meng Huat Tiong, Junnan Li, Guosheng Lin, Boyang Li, Caiming Xiong, Steven C. H. Hoi

ICCL interpolates two images from a class-agnostic sampler and a class-aware sampler, and trains the model such that the representation of the interpolative image can be used to retrieve the centroids for both source classes.

Contrastive Learning Image Classification +1

Cascaded Fast and Slow Models for Efficient Semantic Code Search

no code implementations15 Oct 2021 Akhilesh Deepak Gotmare, Junnan Li, Shafiq Joty, Steven C. H. Hoi

The goal of natural language semantic code search is to retrieve a semantically relevant code snippet from a fixed set of candidates using a natural language query.

Code Search Re-Ranking

Learning Structural Representations for Recipe Generation and Food Retrieval

no code implementations4 Oct 2021 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

Our approach brings together several novel ideas in a systematic framework: (1) exploiting an unsupervised learning approach to obtain the sentence-level tree structure labels before training; (2) generating trees of target recipes from images with the supervision of tree structure labels learned from (1); and (3) integrating the learned tree structures into the recipe generation and food cross-modal retrieval procedure.

Cross-Modal Retrieval Image Captioning +1

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

2 code implementations EMNLP 2021 Yue Wang, Weishi Wang, Shafiq Joty, Steven C. H. Hoi

We present CodeT5, a unified pre-trained encoder-decoder Transformer model that better leverages the code semantics conveyed from the developer-assigned identifiers.

Clone Detection Code Generation +5

Cross-Modal Graph with Meta Concepts for Video Captioning

no code implementations14 Aug 2021 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

Video captioning targets interpreting the complex visual contents as text descriptions, which requires the model to fully understand video scenes including objects and their interactions.

object-detection Object Detection +1

Cycle-Consistent Inverse GAN for Text-to-Image Synthesis

no code implementations3 Aug 2021 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

In this paper, we propose a novel unified framework of Cycle-consistent Inverse GAN (CI-GAN) for both text-to-image generation and text-guided image manipulation tasks.

Image Manipulation Text to image generation +1

$C^3$: Compositional Counterfactual Constrastive Learning for Video-grounded Dialogues

no code implementations16 Jun 2021 Hung Le, Nancy F. Chen, Steven C. H. Hoi

Video-grounded dialogue systems aim to integrate video understanding and dialogue understanding to generate responses that are relevant to both the dialogue and video context.

Contrastive Learning Dialogue Understanding +1

A Large-Scale Benchmark for Food Image Segmentation

2 code implementations12 May 2021 Xiongwei Wu, Xin Fu, Ying Liu, Ee-Peng Lim, Steven C. H. Hoi, Qianru Sun

Existing food image segmentation models are underperforming due to two reasons: (1) there is a lack of high quality food image datasets with fine-grained ingredient labels and pixel-wise location masks -- the existing datasets either carry coarse ingredient labels or are small in size; and (2) the complex appearance of food makes it difficult to localize and recognize ingredients in food images, e. g., the ingredients may overlap one another in the same image, and the identical ingredient may appear distinctly in different food images.

Ranked #2 on Semantic Segmentation on FoodSeg103 (using extra training data)

Semantic Segmentation

VGNMN: Video-grounded Neural Module Network to Video-Grounded Language Tasks

no code implementations16 Apr 2021 Hung Le, Nancy F. Chen, Steven C. H. Hoi

Neural module networks (NMN) have achieved success in image-grounded tasks such as Visual Question Answering (VQA) on synthetic images.

Information Retrieval Question Answering +1

Weakly Supervised Neuro-Symbolic Module Networks for Numerical Reasoning

no code implementations28 Jan 2021 Amrita Saha, Shafiq Joty, Steven C. H. Hoi

Neural Module Networks (NMNs) have been quite successful in incorporating explicit reasoning as learnable modules in various question answering tasks, including the most generic form of numerical reasoning over text in Machine Reading Comprehension (MRC).

Dependency Parsing Language Modelling +2

Weakly-Supervised Multi-Face 3D Reconstruction

1 code implementation6 Jan 2021 Jialiang Zhang, Lixiang Lin, Jianke Zhu, Steven C. H. Hoi

3D face reconstruction plays a very important role in many real-world multimedia applications, including digital entertainment, social media, affection analysis, and person identification.

3D Face Reconstruction 3D Reconstruction +3

Learning Transferrable Parameters for Long-tailed Sequential User Behavior Modeling

no code implementations22 Oct 2020 Jianwen Yin, Chenghao Liu, Weiqing Wang, Jianling Sun, Steven C. H. Hoi

Sequential user behavior modeling plays a crucial role in online user-oriented services, such as product purchasing, news feed consumption, and online advertising.

Transfer Learning

BiST: Bi-directional Spatio-Temporal Reasoning for Video-Grounded Dialogues

1 code implementation EMNLP 2020 Hung Le, Doyen Sahoo, Nancy F. Chen, Steven C. H. Hoi

Video-grounded dialogues are very challenging due to (i) the complexity of videos which contain both spatial and temporal variations, and (ii) the complexity of user utterances which query different segments and/or different objects in videos over multiple dialogue turns.

Response Selection for Multi-Party Conversations withDynamic Topic Tracking

no code implementations15 Oct 2020 Weishi Wang§, Shafiq Joty§, Steven C. H. Hoi

While participants in a multi-party multi-turn conversation simultaneously engage in multiple conversation topics, existing response selection methods are developed mainly focusing on a two-party single-conversation scenario.

Disentanglement Multi-Task Learning +1

Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading

1 code implementation EMNLP 2020 Yifan Gao, Chien-Sheng Wu, Jingjing Li, Shafiq Joty, Steven C. H. Hoi, Caiming Xiong, Irwin King, Michael R. Lyu

Based on the learned EDU and entailment representations, we either reply to the user our final decision "yes/no/irrelevant" of the initial question, or generate a follow-up question to inquiry more information.

Decision Making Discourse Segmentation +2

MoPro: Webly Supervised Learning with Momentum Prototypes

1 code implementation ICLR 2021 Junnan Li, Caiming Xiong, Steven C. H. Hoi

We propose momentum prototypes (MoPro), a simple contrastive learning method that achieves online label noise correction, out-of-distribution sample removal, and representation learning.

Contrastive Learning Image Classification +2

Structure-Aware Generation Network for Recipe Generation from Images

1 code implementation ECCV 2020 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

We investigate an open research task of generating cooking instructions based on only food images and ingredients, which is similar to the image captioning task.

Image Captioning Recipe Generation

Bilevel Continual Learning

1 code implementation30 Jul 2020 Quang Pham, Doyen Sahoo, Chenghao Liu, Steven C. H. Hoi

Continual learning aims to learn continuously from a stream of tasks and data in an online-learning fashion, being capable of exploiting what was learned previously to improve current and future tasks while still being able to perform well on the previous tasks.

Bilevel Optimization Continual Learning +3

Decomposing Generation Networks with Structure Prediction for Recipe Generation

no code implementations27 Jul 2020 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

Recipe generation from food images and ingredients is a challenging task, which requires the interpretation of the information from another modality.

Image Captioning Recipe Generation

Multi-label Thoracic Disease Image Classification with Cross-Attention Networks

no code implementations21 Jul 2020 Congbo Ma, Hu Wang, Steven C. H. Hoi

Automated disease classification of radiology images has been emerging as a promising technique to support clinical diagnosis and treatment planning.

Classification General Classification +2

Adaptive Task Sampling for Meta-Learning

no code implementations ECCV 2020 Chenghao Liu, Zhihao Wang, Doyen Sahoo, Yuan Fang, Kun Zhang, Steven C. H. Hoi

Meta-learning methods have been extensively studied and applied in computer vision, especially for few-shot classification tasks.

Classification General Classification +1

Theory-Inspired Path-Regularized Differential Network Architecture Search

1 code implementation NeurIPS 2020 Pan Zhou, Caiming Xiong, Richard Socher, Steven C. H. Hoi

Then we propose a theory-inspired path-regularized DARTS that consists of two key modules: (i) a differential group-structured sparse binary gate introduced for each operation to avoid unfair competition among operations, and (ii) a path-depth-wise regularization used to incite search exploration for deep architectures that often converge slower than shallow ones as shown in our theory and are not well explored during the search.

Image Classification

Video-Grounded Dialogues with Pretrained Generation Language Models

no code implementations ACL 2020 Hung Le, Steven C. H. Hoi

Pre-trained language models have shown remarkable success in improving various downstream NLP tasks due to their ability to capture dependencies in textual data and generate natural responses.

Dynamics 1

EMT: Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading

1 code implementation26 May 2020 Yifan Gao, Chien-Sheng Wu, Shafiq Joty, Caiming Xiong, Richard Socher, Irwin King, Michael R. Lyu, Steven C. H. Hoi

The goal of conversational machine reading is to answer user questions given a knowledge base text which may require asking clarification questions.

Decision Making Reading Comprehension

Prototypical Contrastive Learning of Unsupervised Representations

3 code implementations ICLR 2021 Junnan Li, Pan Zhou, Caiming Xiong, Steven C. H. Hoi

This paper presents Prototypical Contrastive Learning (PCL), an unsupervised representation learning method that addresses the fundamental limitations of instance-wise contrastive learning.

Contrastive Learning Representation Learning +3

UniConv: A Unified Conversational Neural Architecture for Multi-domain Task-oriented Dialogues

1 code implementation EMNLP 2020 Hung Le, Doyen Sahoo, Chenghao Liu, Nancy F. Chen, Steven C. H. Hoi

Building an end-to-end conversational agent for multi-domain task-oriented dialogues has been an open challenge for two main reasons.

Dialogue State Tracking

VD-BERT: A Unified Vision and Dialog Transformer with BERT

1 code implementation EMNLP 2020 Yue Wang, Shafiq Joty, Michael R. Lyu, Irwin King, Caiming Xiong, Steven C. H. Hoi

By contrast, in this work, we propose VD-BERT, a simple yet effective framework of unified vision-dialog Transformer that leverages the pretrained BERT language models for Visual Dialog tasks.

Answer Generation Visual Dialog

Learning Video Object Segmentation from Unlabeled Videos

1 code implementation CVPR 2020 Xiankai Lu, Wenguan Wang, Jianbing Shen, Yu-Wing Tai, David Crandall, Steven C. H. Hoi

We propose a new method for video object segmentation (VOS) that addresses object pattern learning from unlabeled videos, unlike most existing methods which rely heavily on extensive annotated data.

Representation Learning Semantic Segmentation +3

Cross-Modal Food Retrieval: Learning a Joint Embedding of Food Images and Recipes with Semantic Consistency and Attention Mechanism

no code implementations9 Mar 2020 Hao Wang, Doyen Sahoo, Chenghao Liu, Ke Shu, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi

Food retrieval is an important task to perform analysis of food-related information, where we are interested in retrieving relevant information about the queried food item such as ingredients, cooking instructions, etc.

Cross-Modal Retrieval

Non-Autoregressive Dialog State Tracking

1 code implementation ICLR 2020 Hung Le, Richard Socher, Steven C. H. Hoi

Recent efforts in Dialogue State Tracking (DST) for task-oriented dialogues have progressed toward open-vocabulary or generation-based approaches where the models can generate slot value candidates from the dialogue history itself.

Dialogue State Tracking Multi-domain Dialogue State Tracking +1

Tree-structured Attention with Hierarchical Accumulation

no code implementations ICLR 2020 Xuan-Phi Nguyen, Shafiq Joty, Steven C. H. Hoi, Richard Socher

Incorporating hierarchical structures like constituency trees has been shown to be effective for various natural language processing (NLP) tasks.

Natural Language Processing Text Classification +1

Deep Learning for Person Re-identification: A Survey and Outlook

3 code implementations13 Jan 2020 Mang Ye, Jianbing Shen, Gaojie Lin, Tao Xiang, Ling Shao, Steven C. H. Hoi

The widely studied closed-world setting is usually applied under various research-oriented assumptions, and has achieved inspiring success using deep learning techniques on a number of datasets.

Cross-Modal Person Re-Identification Metric Learning +2

Detecting Cyberattacks in Industrial Control Systems Using Online Learning Algorithms

no code implementations8 Dec 2019 Guangxia Lia, Yulong Shena, Peilin Zhaob, Xiao Lu, Jia Liu, Yangyang Liu, Steven C. H. Hoi

Similar to other information systems, a significant threat to industrial control systems is the attack from cyberspace---the offensive maneuvers launched by "anonymous" in the digital world that target computer-based assets with the goal of compromising a system's functions or probing for information.

Continuous Control Intrusion Detection +1

Attribute-aware Pedestrian Detection in a Crowd

1 code implementation21 Oct 2019 Jialiang Zhang, Lixiang Lin, Yang Li, Yun-chen Chen, Jianke Zhu, Yao Hu, Steven C. H. Hoi

To tackle this critical problem, we propose an attribute-aware pedestrian detector to explicitly model people's semantic attributes in a high-level feature detection fashion.

Pedestrian Detection

Meta-RCNN: Meta Learning for Few-Shot Object Detection

no code implementations25 Sep 2019 Xiongwei Wu, Doyen Sahoo, Steven C. H. Hoi

Specifically, Meta-RCNN learns an object detector in an episodic learning paradigm on the (meta) training data.

Few-Shot Object Detection Meta-Learning +2

Recent Advances in Deep Learning for Object Detection

1 code implementation10 Aug 2019 Xiongwei Wu, Doyen Sahoo, Steven C. H. Hoi

Object detection is a fundamental visual recognition problem in computer vision and has been widely studied in the past decades.

Image Classification object-detection +1

Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems

1 code implementation ACL 2019 Hung Le, Doyen Sahoo, Nancy F. Chen, Steven C. H. Hoi

Developing Video-Grounded Dialogue Systems (VGDS), where a dialogue is conducted based on visual and audio aspects of a given video, is significantly more challenging than traditional image or text-grounded dialogue systems because (1) feature space of videos span across multiple picture frames, making it difficult to obtain semantic information; and (2) a dialogue agent must perceive and process information from different modalities (audio, video, caption, etc.)

Compositional Coding for Collaborative Filtering

1 code implementation9 May 2019 Chenghao Liu, Tao Lu, Xin Wang, Zhiyong Cheng, Jianling Sun, Steven C. H. Hoi

However, CF with binary codes naturally suffers from low accuracy due to limited representation capability in each bit, which impedes it from modeling complex structure of the data.

Collaborative Filtering Recommendation Systems

Learning Cross-Modal Embeddings with Adversarial Networks for Cooking Recipes and Food Images

2 code implementations CVPR 2019 Hao Wang, Doyen Sahoo, Chenghao Liu, Ee-Peng Lim, Steven C. H. Hoi

Food computing is playing an increasingly important role in human daily life, and has found tremendous applications in guiding human behavior towards smart food consumption and healthy lifestyle.

Cross-Modal Retrieval Nutrition +1

Meta-Learning with Domain Adaptation for Few-Shot Learning under Domain Shift

no code implementations ICLR 2019 Doyen Sahoo, Hung Le, Chenghao Liu, Steven C. H. Hoi

Most existing work assumes that both training and test tasks are drawn from the same distribution, and a large amount of labeled data is available in the training tasks.

Domain Adaptation Few-Shot Learning

Deep Learning for Image Super-resolution: A Survey

5 code implementations16 Feb 2019 Zhihao Wang, Jian Chen, Steven C. H. Hoi

Image Super-Resolution (SR) is an important class of image processing techniques to enhance the resolution of images and videos in computer vision.

Image Super-Resolution

Robust Graph Learning from Noisy Data

1 code implementation17 Dec 2018 Zhao Kang, Haiqi Pan, Steven C. H. Hoi, Zenglin Xu

The proposed model is able to boost the performance of data clustering, semisupervised classification, and data recovery significantly, primarily due to two key factors: 1) enhanced low-rank recovery by exploiting the graph smoothness assumption, 2) improved graph construction by exploiting clean data recovered by robust PCA.

General Classification graph construction +6

Adaptive Cost-sensitive Online Classification

no code implementations6 Apr 2018 Peilin Zhao, Yifan Zhang, Min Wu, Steven C. H. Hoi, Mingkui Tan, Junzhou Huang

Cost-Sensitive Online Classification has drawn extensive attention in recent years, where the main approach is to directly online optimize two well-known cost-sensitive metrics: (i) weighted sum of sensitivity and specificity; (ii) weighted misclassification cost.

Anomaly Detection Classification +1

Single-Shot Bidirectional Pyramid Networks for High-Quality Object Detection

no code implementations22 Mar 2018 Xiongwei Wu, Daoxin Zhang, Jianke Zhu, Steven C. H. Hoi

Recent years have witnessed many exciting achievements for object detection using deep learning techniques.

object-detection Object Detection

URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection

4 code implementations9 Feb 2018 Hung Le, Quang Pham, Doyen Sahoo, Steven C. H. Hoi

This approach allows the model to capture several types of semantic information, which was not possible by the existing models.

BIG-bench Machine Learning Feature Engineering +1

Online Learning: A Comprehensive Survey

no code implementations8 Feb 2018 Steven C. H. Hoi, Doyen Sahoo, Jing Lu, Peilin Zhao

Online learning represents an important family of machine learning algorithms, in which a learner attempts to resolve an online prediction (or any type of decision-making) task by learning a model/hypothesis from a sequence of data instances one at a time.

BIG-bench Machine Learning Decision Making +1

Robust Estimation of Similarity Transformation for Visual Object Tracking

2 code implementations14 Dec 2017 Yang Li, Jianke Zhu, Steven C. H. Hoi, Wenjie Song, Zhefeng Wang, Hantang Liu

In order to efficiently search in such a large 4-DoF space in real-time, we formulate the problem into two 2-DoF sub-problems and apply an efficient Block Coordinates Descent solver to optimize the estimation result.

Visual Object Tracking

Feature Agglomeration Networks for Single Stage Face Detection

no code implementations3 Dec 2017 Jialiang Zhang, Xiongwei Wu, Jianke Zhu, Steven C. H. Hoi

In this paper, we propose a novel simple yet effective framework of "Feature Agglomeration Networks" (FANet) to build a new single stage face detector, which not only achieves state-of-the-art performance but also runs efficiently.

Face Detection

Online Deep Learning: Learning Deep Neural Networks on the Fly

3 code implementations10 Nov 2017 Doyen Sahoo, Quang Pham, Jing Lu, Steven C. H. Hoi

Deep Neural Networks (DNNs) are typically trained by backpropagation in a batch learning setting, which requires the entire training data to be made available prior to the learning task.

online learning

Projection-free Distributed Online Learning in Networks

no code implementations ICML 2017 Wenpeng Zhang, Peilin Zhao, Wenwu Zhu, Steven C. H. Hoi, Tong Zhang

The conditional gradient algorithm has regained a surge of research interest in recent years due to its high efficiency in handling large-scale machine learning problems.

online learning

Face Detection using Deep Learning: An Improved Faster RCNN Approach

no code implementations28 Jan 2017 Xudong Sun, Pengcheng Wu, Steven C. H. Hoi

In this report, we present a new face detection scheme using deep learning and achieve the state-of-the-art detection performance on the well-known FDDB face detetion benchmark evaluation.

Face Detection

Malicious URL Detection using Machine Learning: A Survey

1 code implementation25 Jan 2017 Doyen Sahoo, Chenghao Liu, Steven C. H. Hoi

This article aims to provide a comprehensive survey and a structural understanding of Malicious URL Detection techniques using machine learning.

BIG-bench Machine Learning

SOL: A Library for Scalable Online Learning Algorithms

1 code implementation28 Oct 2016 Yue Wu, Steven C. H. Hoi, Chenghao Liu, Jing Lu, Doyen Sahoo, Nenghai Yu

SOL is an open-source library for scalable online learning algorithms, and is particularly suitable for learning with high-dimensional data.

BIG-bench Machine Learning General Classification +2

Online Bayesian Collaborative Topic Regression

no code implementations28 May 2016 Chenghao Liu, Tao Jin, Steven C. H. Hoi, Peilin Zhao, Jianling Sun

In this paper, we propose a novel scheme of Online Bayesian Collaborative Topic Regression (OBCTR) which is efficient and scalable for learning from data streams.

online learning Recommendation Systems

Scalable Image Retrieval by Sparse Product Quantization

no code implementations15 Mar 2016 Qingqun Ning, Jianke Zhu, Zhiyuan Zhong, Steven C. H. Hoi, Chun Chen

Unlike the existing approaches, in this paper, we propose a novel approach called Sparse Product Quantization (SPQ) to encoding the high-dimensional feature vectors into sparse representation.

Content-Based Image Retrieval Quantization

Adaptive Subgradient Methods for Online AUC Maximization

no code implementations1 Feb 2016 Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong

Despite their encouraging results reported, the existing online AUC maximization algorithms often adopt simple online gradient descent approaches that fail to exploit the geometrical knowledge of the data observed during the online learning process, and thus could suffer from relatively larger regret.

online learning

Budget Online Multiple Kernel Learning

no code implementations16 Nov 2015 Jing Lu, Steven C. H. Hoi, Doyen Sahoo, Peilin Zhao

To overcome this drawback, we present a novel framework of Budget Online Multiple Kernel Learning (BOMKL) and propose a new Sparse Passive Aggressive learning to perform effective budget online learning.

General Classification online learning

LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with Deep Region-based Convolutional Networks

no code implementations8 Nov 2015 Steven C. H. Hoi, Xiongwei Wu, Hantang Liu, Yue Wu, Huiqiong Wang, Hui Xue, Qiang Wu

In this paper, we introduce "LOGO-Net", a large-scale logo image database for logo detection and brand recognition from real-world product images.

Logo Recognition object-detection +1

A Framework of Sparse Online Learning and Its Applications

no code implementations25 Jul 2015 Dayong Wang, Pengcheng Wu, Peilin Zhao, Steven C. H. Hoi

Unlike some existing online data stream classification techniques that are often based on first-order online learning, we propose a framework of Sparse Online Classification (SOC) for data stream classification, which includes some state-of-the-art first-order sparse online learning algorithms as special cases and allows us to derive a new effective second-order online learning algorithm for data stream classification.

Anomaly Detection Classification +2

Reliable Patch Trackers: Robust Visual Tracking by Exploiting Reliable Patches

no code implementations CVPR 2015 Yang Li, Jianke Zhu, Steven C. H. Hoi

Most modern trackers typically employ a bounding box given in the first frame to track visual objects, where their tracking results are often sensitive to the initialization.

Visual Tracking

Large-scale Online Feature Selection for Ultra-high Dimensional Sparse Data

no code implementations27 Sep 2014 Yue Wu, Steven C. H. Hoi, Tao Mei, Nenghai Yu

However, unlike many second-order learning methods that often suffer from extra high computational cost, we devise a novel smart algorithm for second-order online feature selection using a MaxHeap-based approach, which is not only more effective than the existing first-order approaches, but also significantly more efficient and scalable for large-scale feature selection with ultra-high dimensional sparse data, as validated from our extensive experiments.

feature selection

Online Portfolio Selection: A Survey

2 code implementations10 Dec 2012 Bin Li, Steven C. H. Hoi

This article aims to provide a timely and comprehensive survey for both machine learning and data mining researchers in academia and quantitative portfolio managers in the financial industry to help them understand the state-of-the-art and facilitate their research and practical applications.

BIG-bench Machine Learning Meta-Learning

PAMR: Passive aggressive mean reversion strategy for portfolio selection

1 code implementation Machine Learning 2012 Bin Li, Peilin Zhao, Steven C. H. Hoi

This article proposes a novel online portfolio selection strategy named “Passive Aggressive Mean Reversion” (PAMR).

CORN: Correlation-driven Non parametric Learning Approach for Portfolio Selection

1 code implementation ACM Transactions on Intelligent Systems and Technology. 2 2011 Bin Li, Steven C. H. Hoi, Vivekanand GOPALKRISHNAN

Machine learning techniques have been adopted to select portfolios from financial markets in some emerging intelligent business applications.

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