Tootfinder

A novel decision fusion approach for sale price prediction using Elastic Net and MOPSO
Amir Eshaghi Chaleshtori
https://arxiv.org/abs/2403.20033 https://…

A novel decision fusion approach for sale price prediction using Elastic Net and MOPSO
Price prediction algorithms propose prices for every product or service according to market trends, projected demand, and other characteristics, including government rules, international transactions, and speculation and expectation. As the dependent variable in price prediction, it is affected by several independent and correlated variables which may challenge the price prediction. To overcome this challenge, machine learning algorithms allow more accurate price prediction without explicitly m…

This https://arxiv.org/abs/2301.03553 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

FedDebug: Systematic Debugging for Federated Learning Applications
In Federated Learning (FL), clients independently train local models and share them with a central aggregator to build a global model. Impermissibility to access clients' data and collaborative training make FL appealing for applications with data-privacy concerns, such as medical imaging. However, these FL characteristics pose unprecedented challenges for debugging. When a global model's performance deteriorates, identifying the responsible rounds and clients is a major pain point. Developers …

Time For 9 o'clock #HashTagGames hosted by @…
Celebrities have ice cream, pizzas and even cheeseburgers combos named after them that highlight their characteristics. Some brand food items after themselves. What about fictional characters? Let's play!
#FoodsNamedAfterCharacters
#HashTagGames
How to play: Write something, Use the HashTag, Toot/Post and Repeat!
Hint: Can be TV, movie, book, song, or other fictional characters

This https://arxiv.org/abs/2403.08505 has been replaced.
link: https://scholar.google.com/scholar?q=a

Content-aware Masked Image Modeling Transformer for Stereo Image Compression
Existing learning-based stereo image codec adopt sophisticated transformation with simple entropy models derived from single image codecs to encode latent representations. However, those entropy models struggle to effectively capture the spatial-disparity characteristics inherent in stereo images, which leads to suboptimal rate-distortion results. In this paper, we propose a stereo image compression framework, named CAMSIC. CAMSIC independently transforms each image to latent representation and…

Time For 9 o'clock #HashTagGames hosted by @…
Celebrities have ice cream, pizzas and even cheeseburgers combos named after them that highlight their characteristics. Some brand food items after themselves. What about fictional characters? Let's play!
#FoodsNamedAfterCharacters
#HashTagGames
How to play: Write something, Use the HashTag, Toot/Post and Repeat!
Hint: Can be TV, movie, book, song, or other fictional characters

Strength Lies in Differences! Towards Effective Non-collaborative Dialogues via Tailored Strategy Planning
Tong Zhang, Chen Huang, Yang Deng, Hongru Liang, Jia Liu, Zujie Wen, Wenqiang Lei, Tat-Seng Chua
https://arxiv.org/abs/2403.06769

Strength Lies in Differences! Towards Effective Non-collaborative Dialogues via Tailored Strategy Planning
We investigate non-collaborative dialogue agents that must engage in tailored strategic planning for diverse users to secure a favorable agreement. This poses challenges for existing dialogue agents due to two main reasons: their inability to integrate user-specific characteristics into their strategic planning and their training paradigm's failure to produce strategic planners that can generalize to diverse users. To address these challenges, we propose TRIP to enhance the capability in tailor…

This https://arxiv.org/abs/2403.14176 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

ReFeree: Radar-based efficient global descriptor using a Feature and Free space for Place Recognition
Radar is highlighted for robust sensing capabilities in adverse weather conditions (e.g. dense fog, heavy rain, or snowfall). In addition, Radar can cover wide areas and penetrate small particles. Despite these advantages, Radar-based place recognition remains in the early stages compared to other sensors due to its unique characteristics such as low resolution, and significant noise. In this paper, we propose a Radarbased place recognition utilizing a descriptor called ReFeree using a feature …

Event Cameras Meet SPADs for High-Speed, Low-Bandwidth Imaging
Manasi Muglikar, Siddharth Somasundaram, Akshat Dave, Edoardo Charbon, Ramesh Raskar, Davide Scaramuzza
https://arxiv.org/abs/2404.11511

Event Cameras Meet SPADs for High-Speed, Low-Bandwidth Imaging
Traditional cameras face a trade-off between low-light performance and high-speed imaging: longer exposure times to capture sufficient light results in motion blur, whereas shorter exposures result in Poisson-corrupted noisy images. While burst photography techniques help mitigate this tradeoff, conventional cameras are fundamentally limited in their sensor noise characteristics. Event cameras and single-photon avalanche diode (SPAD) sensors have emerged as promising alternatives to conventiona…

MM-Gaussian: 3D Gaussian-based Multi-modal Fusion for Localization and Reconstruction in Unbounded Scenes
Chenyang Wu, Yifan Duan, Xinran Zhang, Yu Sheng, Jianmin Ji, Yanyong Zhang
https://arxiv.org/abs/2404.04026

MM-Gaussian: 3D Gaussian-based Multi-modal Fusion for Localization and Reconstruction in Unbounded Scenes
Localization and mapping are critical tasks for various applications such as autonomous vehicles and robotics. The challenges posed by outdoor environments present particular complexities due to their unbounded characteristics. In this work, we present MM-Gaussian, a LiDAR-camera multi-modal fusion system for localization and mapping in unbounded scenes. Our approach is inspired by the recently developed 3D Gaussians, which demonstrate remarkable capabilities in achieving high rendering quality…