arXiv:2502.05459v2 Announce Type: replace-cross Abstract: White blood cells (WBC) are important parts of our immune system, and they protect our body against infections by eliminating viruses, bacteria, parasites and fungi. The number of WBC types and the total number of WBCs provide important information about our health status. A traditional method, convolutional neural networks (CNN), a deep learning architecture, can classify the blood cell from a part of an object and perform object recognition. Various CNN models exhibit […]

Ver mais

arXiv:2604.20847v1 Announce Type: new Abstract: Music Recommendation Systems (MRSs) are a cornerstone of modern streaming platforms. Existing recommendation models, spanning both recall and ranking stages, predominantly rely on collaborative filtering, which fails to exploit the intrinsic characteristics of audio and consequently leads to suboptimal performance, particularly in cold-start scenarios. However, existing music recommendation datasets often lack rich multimodal information, such as raw audio signals and descriptive textual metadata. Moreover, current recommender system evaluation frameworks remain inadequate, as they […]

Ver mais

arXiv:2601.12231v1 Announce Type: new Abstract: Insider threat detection is a key challenge in enterprise security, relying on user activity logs that capture rich and complex behavioral patterns. These logs are often multi-channel, non-stationary, and anomalies are rare, making anomaly detection challenging. To address these issues, we propose a novel framework that integrates wavelet-aware modulation, multi-resolution wavelet decomposition, and resolution-adaptive attention for robust anomaly detection. Our approach first applies a deviation-aware modulation scheme to suppress routine behaviors while amplifying […]

Ver mais

arXiv:2604.07515v1 Announce Type: new Abstract: We develop the first theoretically-efficient algorithm for maintaining the maximal independent set (MIS) of a graph in the parallel batch-dynamic setting. In this setting, a graph is updated with batches of edge insertions/deletions, and for each batch a parallel algorithm updates the maximal independent set to agree with the new graph. A batch-dynamic algorithm is considered efficient if it is work efficient (i.e., does no more asymptotic work than applying the updates sequentially) […]

Ver mais

Efficient brain tumor diagnosis is crucial for early treatment; however, it is challenging because of lesion variability and image complexity. We evaluated convolutional neural networks (CNNs) in a federated learning (FL) setting, comparing models trained on original versus preprocessed MRI images (resizing, grayscale conversion, normalization, filtering, and histogram equalization). Preprocessing alone yielded negligible gains; combined with test-time augmentation (TTA), it delivered consistent, statistically significant improvements in federated MRI classification (p<0.001). In practice, TTA should be the default inference […]

Ver mais

arXiv:2601.09750v1 Announce Type: new Abstract: Large language models (LLMs) have proven to work well in question-answering scenarios, but real-world applications often require access to tools for live information or actuation. For this, LLMs can be extended with tools, which are often defined in advance, also allowing for some fine-tuning for specific use cases. However, rapidly evolving software landscapes and individual services require the constant development and integration of new tools. Domain- or company-specific tools can greatly elevate the […]

Ver mais

In this tutorial: You will understand that Exploration vs Exploitation is not a button, it is not “epsilon“, but a real data collection strategy, which decides what the agent can learn and how good it can become. You will see why the training reward can lie to you, why an agent without exploration can look “better” on the graph, but actually be weaker in reality. You will learn where exploration actually occurs in an Markov Decision Process(MDP), not […]

Ver mais

Retail’s brick-and-mortar resurgence is a lesson in how to reassess assets previously seen as liabilities.

Ver mais