69,161 Result(s)
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Chapter
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Algorithm Analysis and Problem Complexity
Artificial Intelligence
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Chapter and Conference Paper
DiffMoCa: Diffusion Model Based Multi-modality Cut and Paste
The Multi-mOdality Cut and pAste (MoCa) method cuts data from other frames and pastes it onto the current training data frame to increase the number of training object samples. However, the samples used by MoC...
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Chapter and Conference Paper
Geometrically-Aware Dual Transformer Encoding Visual and Textual Features for Image Captioning
When describing pictures from the point of view of human observers, the tendency is to prioritize eye-catching objects, link them to corresponding labels, and then integrate the results with background informa...
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Chapter and Conference Paper
Interpreting Pretrained Language Models via Concept Bottlenecks
Pretrained language models (PLMs) have made significant strides in various natural language processing tasks. However, the lack of interpretability due to their “black-box” nature poses challenges for responsi...
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Chapter and Conference Paper
A Weighted Cross-Modal Feature Aggregation Network for Rumor Detection
In this paper, we propose a Weighted Cross-modal Aggregation network (WCAN) for rumor detection in order to combine highly correlated features in different modalities and obtain a unified representation in the...
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Chapter and Conference Paper
An Empirical Analysis of Gumbel MuZero on Stochastic and Deterministic Einstein Würfelt Nicht!
MuZero and its successors, Gumbel MuZero and Stochastic MuZero, have achieved superhuman performance in many domains. MuZero combines Monte Carlo tree search and model-based reinforcement learning, which allow...
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Chapter and Conference Paper
Efficient 3D View Synthesis from Single-Image Utilizing Diffusion Priors
In this paper, we introduce a novel framework for synthesizing novel views of objects from a single image. Leveraging the capabilities of fine-tuned diffusion models, our method combines latent 3D knowledge as...
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Chapter and Conference Paper
Ranking Enhanced Supervised Contrastive Learning for Regression
Supervised contrastive learning has shown promising results in image classification tasks where the representations are pulled together if they share same labels or otherwise pushed apart. Such dispersion proc...
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Chapter
The Practical Concepts of Machine Learning
Patanjali Kashyapa*
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Chapter and Conference Paper
GraphNILM: A Graph Neural Network for Energy Disaggregation
Non-Intrusive Load Monitoring (NILM) remains a critical issue in both commercial and residential energy management, with a key challenge being the requirement for individual appliance-specific deep learning mo...
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Chapter and Conference Paper
Soft Contrastive Learning for Implicit Feedback Recommendations
Collaborative filtering (CF) plays a crucial role in the development of recommendations. Most CF research focuses on implicit feedback due to its accessibility, but deriving user preferences from such feedback...
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Chapter and Conference Paper
Distributional Kernel: An Effective and Efficient Means for Trajectory Retrieval
In this paper, we propose a new and powerful way to represent trajectories and measure the distance between them using a distributional kernel. Our method has two unique properties: (i) the identity property w...
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Chapter and Conference Paper
A Deep Learning Approach for Single-Cell Perturbation Prediction Using Small Molecule Chemical Structures
In this study, we develop a deep learning framework aimed at predicting the impacts of chemical perturbations on individual cells, emphasizing the encoding of small molecular chemical structures . Utilizing th...
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Chapter
Constrained Optimization
In this chapter, we will introduce the concept of (COPs), commonly used constraint-handling techniques based on EAs, and future research on constrained optimization.
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Chapter and Conference Paper
A Robust Two-Stage Model for the Urban Air Mobility Flight Scheduling Problem
Thanks to recent technical progress, it is now possible to consider air mobility for people at the scale of a city. In this work, we focus on a robust strategic planning problem in an urban air mobility contex...
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Chapter and Conference Paper
Day-Ahead Lot-Sizing Under Uncertainty: An Application to Green Hydrogen Production
This work investigates the short-term production planning of green hydrogen obtained through water electrolysis using electricity from a wind power source and a connection to the national electricity grid. Ele...
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Chapter and Conference Paper
Robust Influence-Based Training Methods for Noisy Brain MRI
Correctly classifying brain tumors is imperative to the prompt and accurate treatment of a patient. While several classification algorithms based on classical image processing or deep learning methods have bee...
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Chapter and Conference Paper
Dfp-Unet: A Biomedical Image Segmentation Method Based on Deformable Convolution and Feature Pyramid
U-net is a classic deep network framework in the field of biomedical image segmentation, which uses a U-shaped encoder and decoder structure to realize the recognition and segmentation of semantic features, bu...
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Chapter and Conference Paper
Evolving Super Graph Neural Networks for Large-Scale Time-Series Forecasting
Graph Recurrent Neural Networks (GRNN) excel in time-series prediction by modeling complicated non-linear relationships among time-series. However, most GRNN models target small datasets that only have tens of...
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Chapter and Conference Paper
Kernel Representation Learning with Dynamic Regime Discovery for Time Series Forecasting
Correlations between variables in complex ecosystems such as weather and financial markets lead to a great amount of dynamic and co-evolving time series data, posing a significant challenge to the current fore...
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Chapter and Conference Paper
SATJiP: Spatial and Augmented Temporal Jigsaw Puzzles for Video Anomaly Detection
Video Anomaly Detection (VAD) is a significant task, which refers to taking a video clip as input and outputting class labels, e.g., normal or abnormal, at the frame level. Wang et al. proposed a method called...
