Is the war entering a new phase? Polls have closed in Russia's first wartime parliamentary elections, with the ruling United Russia party on course to win the tightly controlled vote. The Kremlin wants the elections, the first parliamentary vote since the start of the full-scale invasion of Ukraine in 2022, to showcase popular support for the war and legitimise its action. The drone strikes on Sunday killed at least three people in the Moscow region and two more in the Russian-held part of Ukraine's Kherson region, including an election official, according to the region's governor and the election commission. Russian authorities also reported attacks on the country's electronic voting systems and communication lines during the polls, but said the electoral process was mostly smooth.

DOJ charged 16 people in multiple states for alleged illegal voting, noncitizen voting and voter registration fraud in connection with the 2022 and 2024 elections.

Trump has touted a recent Census report. WIRED found grave flaws in its analysis and the process behind it, and confirmed the identity of several of its authors--among them a one-time DOGE affiliate. A report published by the US Census Bureau last month purported to uncover evidence backing up President Donald Trump's baseless claims that noncitizens voting cost him the 2020 election . It was the latest salvo in Trump's broader assault on the safety of US elections. "I WON THE ELECTION," Trump quickly declared on Truth Social after the publication of the report.

Decision tree (and its extensions such as Gradient Boosting Decision Trees and Random Forest) is a widely used machine learning algorithm, due to its practical effectiveness and model interpretability. With the emergence of big data, there is an increasing need to parallelize the training process of decision tree. However, most existing attempts along this line suffer from high communication costs. In this paper, we propose a new algorithm, called Parallel Voting Decision Tree (PV-Tree), to tackle this challenge. After partitioning the training data onto a number of (e.g., M) machines, this algorithm performs both local voting and global voting in each iteration.

Decision tree (and its extensions such as Gradient Boosting Decision Trees and Random Forest) is a widely used machine learning algorithm, due to its practical effectiveness and model interpretability. With the emergence of big data, there is an increasing need to parallelize the training process of decision tree. However, most existing attempts along this line suffer from high communication costs. In this paper, we propose a new algorithm, called \emph{Parallel Voting Decision Tree (PV-Tree)}, to tackle this challenge. After partitioning the training data onto a number of (e.g., $M$) machines, this algorithm performs both local voting and global voting in each iteration.

A typical solution isdirect democracywhich decides based on amajority vote, the so called "wisdom of the crowd."

The US Department of Justice (DOJ) has removed thousands of documents related to Jeffrey Epstein from its website after victims said their identities had been compromised. Lawyers for Epstein's victims said flawed redactions in the files released on Friday had turned upside down the lives of nearly 100 survivors. Email addresses and nude photos in which the names and faces of potential victims could be identified were included in the release. Survivors issued a statement calling the disclosure outrageous and said they should not be named, scrutinized and retraumatized. The DOJ said it had taken down all the flagged files and that mistakes were due to technical or human error.

Decision tree (and its extensions such as Gradient Boosting Decision Trees and Random Forest) is a widely used machine learning algorithm, due to its practical effectiveness and model interpretability. With the emergence of big data, there is an increasing need to parallelize the training process of decision tree. However, most existing attempts along this line suffer from high communication costs. In this paper, we propose a new algorithm, called \emph{Parallel Voting Decision Tree (PV-Tree)}, to tackle this challenge. After partitioning the training data onto a number of (e.g., $M$) machines, this algorithm performs both local voting and global voting in each iteration.