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Recent trends focus on incentivizing consumers to reduce their demand consumption during peak hours for sustainable demand response. To minimize the loss, the distributor companies should target the right set of consumers and demand the right ...$$

Civic crowdfunding (CC) is a popular medium for raising funds for public projects from interested agents. With Blockchains gaining traction, we can implement CC reliably and transparently with smart contracts (SCs). The fundamental challenge in CC ...

Federated learning suffers from terrible generalization performance because the model fails to utilize global information over all clients when data is non-IID (not independently or identically distributed) partitioning. Meanwhile, the theoretical ...

We consider a fixed-price mechanism design setting where a seller sells one item via a social network. Each buyer in the network has a valuation of the item independently derived from a given continuous distribution. Initially, the seller can only ...

This paper introduces a new online learning framework for multiclass classification called learning with diluted bandit feedback. At every time step, the algorithm predicts a candidate label set instead of a single label for the observed example. ...$\mathcal{}{}^{\mathrm{}\frac{\mathrm{}}{\mathrm{}}}$

A common assumption in game theory is that players have a common and correct (albeit not always complete) knowledge with regards to the abstract formulation of the game. However, in many real-world situations it could be the case that (some of) ...

We propose a novel approach to building influence-driven explanations (IDXs) for (discrete) Bayesian network classifiers (BCs). IDXs feature two main advantages wrt other commonly adopted explanation methods First, IDXs may be generated using the (...

We study the excludable public project model where the decision is binary (build or not build). In a classic excludable and binary public project model, an agent either consumes the project in its whole or is completely excluded. We study a ...

Most studies of facility location problems permit a facility to be located at any position. In practice, this may not be possible. For instance, we might have to limit facilities to particular locations such as at highway exits, close to bus stops,...

Existing face sketch synthesis methods extend conditional generative adversarial network framework with promising performance. However, they usually pre-train on additional large-scale datasets, and the performance is still not satisfied. To ...

Scene text detection in the wild is a hot research area in the field of computer vision, which has achieved great progress with the aid of deep learning. However, training deep text detection models needs large amounts of annotations such as ...

Planning an obstacle-free optimal path presents great challenges for mobile robot applications, the deep deterministic policy gradient (DDPG) algorithm offers an effective solution. However, when the original DDPG is applied to robot path planning,...

Visual reasoning and reconsidering capabilities are instinctively executed alternately as people watch a video and attempt to describe its contents with natural language. Inspired by this, a novel network that joints fully dynamic context guided ...

The prediction of hip joint center (HJC) is an important step in hip dysplasia screening. Existing state-of-the-art identification methods focus on the development of Mose circle, functional and predictive methods. Those approaches extract few ...

Image captioning methods with attention mechanism are leading this field, especially models with global and local attention. But there are few conventional models to integrate the relationship information between various regions of the image. In ...

Software usually provides different GUI layouts for different devices for a better user experience. This increases the workload of testing, so crowdsourced testing is needed to reduce costs. The crowdsourced testing will perform similar test steps ...

Aiming at the current YOLOv4-tiny network’s insufficient feature fusion capability and low utilization of feature extraction in flame and smoke detection tasks, a flame and smoke detection algorithm based on improved YOLOv4-tiny is proposed. ...

Protein Structure Prediction (PSP) is one of the most challenging problems in bioinformatics and biomedicine. PSP has obtained significant improvement lately. This is from the growth of the protein data bank (PDB) and the use of Deep Neural ...$$$$$$$$

This paper builds an interactive automatic picture editing system based on the most advanced algorithms in the field of multi-modality. It removes a specific area or entity in the image according to the natural language expression, which is like a ...

Micro-expression recognition is a video sentiment classification task with extremely small sample size. The transience and spatial locality of micro-expressions bring difficulties to constructing large micro-expression databases and designing ...

Accurate identification and early diagnosis of malignant pulmonary nodules are critical to improving the survival rate of lung cancer patients. Recently, deep learning methods have been proved to be successful in computer-aided diagnosis tasks. ...

Pedestrian detection under occlusion scenes remains a formidable challenge in computer vision. Recently, anchor-free approach has been raised on the object detection and pedestrian detection field, anchor-free detector Center and Scale Prediction (...

Documents often contain complex physical structures, which make the Document Layout Analysis (DLA) task challenging. As a pre-processing step for content extraction, DLA has the potential to capture rich information in historical or scientific ...

From a dataset, one can construct different machine learning (ML) models with different parameters and/or inductive biases. Although these models give similar prediction performances when tested on data that are currently available, they may not ...

Digital camouflage is the most common and effective means to combat military reconnaissance. Traditional digital camouflage generation methods must regenerate camouflage images according to the current environment. When the environment changes, ...

In this paper, we address the problem of clustering earthquakes in a catalog, which is also known as declustering in seismology, i.e., a task of classifying each earthquake into foreshock, mainshock, or aftershock. For this purpose, we newly ...$$