Home Knowledge Base Big Data

Big Data

No mentions found

This entity hasn't been tracked yet, or Iris is still building its knowledge base.

Related Articles from SNS

As Big Tech’s power demand surges, data centers bring utilities a huge new profit center

The market hasn’t fully priced the next logical step for the AI buildout: Big Tech acquiring regulated utilities outright.

MarketWatch 10d ago

$O(n +f(k))$: Truly Linear FPT

Announce Type: new Abstract: Parameterized complexity has always been concerned with practical computing: by confining combinatorial explosion to a secondary parameter $k$, one can uncover why and how many NP-hard problems are effectively tackled in practice. Today, however, the scale of data has changed: scientists study Big Data, which is so large that even quadratic dependence in the total input size $n$ is unaffordable. Therefore, what constitutes a practical algorithm has also changed.

arXiv CS 8d ago

An Ensembled Latent Factor Model via Differential Evolution and Gradient Descent Optimization

arXiv:2606.04408v1 Announce Type: new Abstract: High-dimensional and incomplete (HDI) data are prevalent in many real-world big data scenarios. Latent factor models serve as a common representation learning approach, capable of uncovering informative latent factors from such data.

arXiv CS 6d ago

Modeling and Optimization for Massive Data Allocation in Database

new Abstract: In the era of big data, e-commerce and Internet platforms face the challenge of processing massive amounts of data. However, due to data being scattered across different machines in distributed database, extra communication costs are incurred in gathering relevant data to complete transactions. Without a carefully designed data placement scheme, this cost can severely impact the performance of Online Transaction Processing systems.

arXiv CS 9d ago

Kore: Binary File Format Optimized for Modern Data Systems (Open Source)

The fastest, most compressed columnar format for big data | v0.1.0 KORE is a high-performance binary file format optimized for analytical workloads. It provides: - 38% compression ratio (vs 63% for Parquet) - 131x query speedup with column pruning & predicate pushdown - Zero data loss verification (400K+ cells tested) - Native Spark integration — read/write with PySpark Add this crate as a dependency (when published) or include from path: use kore_fileformat::*; // Write data...

Hacker News 10d ago

Massachusetts bans sale of precise location data in new privacy rights bill

Massachusetts lawmakers have voted to pass privacy protections that grant the state’s residents new rights over accessing and deleting their data held by big tech giants. The bill also bans companies from selling their users’ precise location data. Lawmakers in the Massachusetts House passed the state’s Consumer Data Privacy Act in a unanimous 146-0 vote on Thursday, months after all of the Senate’s 40 lawmakers voted in favor of advancing its own bill in September.

Hacker News 1d ago

An efficient grey theory-driven path selection for energy efficiency control in the Internet of Things using fog and cloud computing

arXiv:2510.03533v2 Announce Type: replace Abstract: Due to the big data exchange on the Internet of Things, proper routing and selecting the best routes for fast data transmission improve network performance. There are major challenges, like high delay, when cloud computing is used. Therefore, one solution is to use other schemes, such as fog computing.

arXiv CS 9d ago

Trump’s immigration enforcers look into buying ad data. Industry insiders fear what comes next.

The trillion-dollar industry that amasses and shares troves of Americans’ information is confronting a new ethical quandary — the Trump administration’s interest in wielding this data to potentially further its sweeping immigration agenda. Immigration and Customs Enforcement published a request for information in January seeking input on how “commercial Big Data and Ad Tech providers can directly support investigations,” a request that came as the administration was pursuing...

Politico EU 10d ago

ReSGA: A Large Tail Risk Model for Learning Value-at-Risk and Expected Shortfall

Announce Type: cross Abstract: Learning Value-at-Risk (VaR) and Expected Shortfall (ES) is important for managing financial risks effectively. Existing approaches with limited parameters are vulnerable to model misspecification in the era of big data.

arXiv CS 6d ago

Meta weighs big equity raising to finance AI infrastructure, FT reports

Meta weighs big equity raising to finance AI infrastructure, FT reports June 5 : Meta is considering raising tens of billions of dollars in a stock offering as it seeks new sources of capital to fund the company's AI ambitions, the Financial Times reported on Friday. The report comes after Alphabet moved to raise $84.75 billion in upsized equity offerings, as Big Tech competes to build data centers and capitalize on growing demand for AI. Meta executives have been exploring "creative" ways...

Channel News Asia 4d ago