Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs. (Wikipedia)
In this paper we propose an approximated learning framework for large scale graphical models and derive message passing algorithms for learning their parameters efficiently. We first relate CRFs and structured SVMs and show that in the CRF's primal a variant of the log-partition function, known as soft-max, smoothly approximates the hinge loss function of structured SVMs. We then propose an intuitive approximation for structured prediction problems using Fenchel duality based on a local entropy approximation that computes the exact gradients of the approximated problem and is guaranteed to converge. Unlike existing approaches, this allow us to learn graphical models with cycles and very large number of parameters efficiently. We demonstrate the effectiveness of our approach in an image denoising task.
Model-free Reinforcement Learning (RL) algorithms such as Q-learning [Watkins, Dayan 92] have been widely used in practice and can achieve human level performance in applications such as video games [Mnih et al. 15]. Recently, equipped with the idea of optimism in the face of uncertainty, Q-learning algorithms [Jin, Allen-Zhu, Bubeck, Jordan 18] can be proven to be sample efficient for discrete tabular Markov Decision Processes (MDPs) which have finite number of states and actions. In this work, we present an efficient model-free Q-learning based algorithm in MDPs with a natural metric on the state-action space--hence extending efficient model-free Q-learning algorithms to continuous state-action space. Compared to previous model-based RL algorithms for metric spaces [Kakade, Kearns, Langford 03], our algorithm does not require access to a black-box planning oracle.
KAGOSHIMA - An 18-year-old Japanese teenager, once recognized as having the longest hair in the world among 13-to-17-year-olds, had her first-ever haircut Tuesday before starting life at university. Keito Kawahara, who lives in Izumi, Kagoshima Prefecture, said she plans to donate the hair that was cut for medical wigs. Kawahara initially grew her hair to hide a scar on her head that developed as a result of medical treatment shortly after birth. She continued life without cutting her hair, which she braided every morning during high school. There were times when she thought about changing her hairstyle, but instead she focused on studying for university entrance examinations.
SAN DIEGO - Authorities and family members say a renowned British balloonist and scientist who set 79 world ballooning records died after a balloon-related accident in Southern California. The San Diego Union-Tribune reports Thursday that 74-year-old Julian Richard Nott was injured over the weekend after his balloon with a pressurized cabin landed in a rural area. The newspaper says Nott died Tuesday at a hospital. An obituary on his website says Nott was flying an experimental balloon he invented to test high-altitude technology. San Diego County sheriff's officials say deputies responded Sunday following reports that two people were injured after the aircraft landed near Palomar Mountain.
Elizabeth Keatinge tells us about Elon Musk's DNA Friend makes fun of the at-home DNA testing craze. The government's contempt of court case against Tesla CEO Elon Musk is moving forward. Federal Judge Alison Nathan has set a court date of April 4 to hold oral arguments. The Securities and Exchange Commission is asking Nathan to find Musk in contempt for allegedly violating terms of an October court-approved securities fraud settlement with a Feb. 19 tweet. In the tweet, Musk wrote: "Tesla made 0 cars in 2011, but will make around 500k in 2019."
Numeric representation of Text documents is challenging task in machine learning and there are different ways there to create the numerical features for texts such as vector representation using Bag of Words, Tf-IDF etc.I am not going in detail what are the advantages of one over the other or which is the best one to use in which case. There are lot of good reads available to explain this. It's a Model to create the word embeddings, where it takes input as a large corpus of text and produces a vector space typically of several hundred dimesions. The underlying assumption of Word2Vec is that two words sharing similar contexts also share a similar meaning and consequently a similar vector representation from the model. For instance: "Bank", "money" and "accounts" are often used in similar situations, with similar surrounding words like "dollar", "loan" or "credit", and according to Word2Vec they will therefore share a similar vector representation.
USA TODAY tech expert Jefferson Graham explains the pros and cons of your childrens' favorite apps. TikTok, a popular video-sharing app, has agreed to pay $5.7 million to settle Federal Trade Commission allegations that it illegally collected personal information from children. The FTC's complaint, filed by the Department of Justice, alleged that TikTok, formerly known as Musical.ly, The act requires websites and online services to direct children under 13 to get parental consent before collecting personal information. The operators of the app "knew many children were using the app but they still failed to seek parental consent before collecting names, email addresses, and other personal information from users under the age of 13," FTC Chairman Joe Simons said in a statement Wednesday.
Kyle Busch broke a tie with Ron Hornaday Jr. for the NASCAR Truck Series victory record Saturday at Atlanta Motor Speedway, winning No. 52 in a race delayed by rain with nine laps to go. "It means a lot," Busch said. The first 16 victories came in trucks fielded by Billy Ballew before Busch founded his own Kyle Busch Motorsports team. With Ballew in attendance at Atlanta, Busch's Tundra carried the former owner's name. "I had Billy Ballew on board with us here today," Busch said.
As always, it depends, if we are talking about few jobs then maybe Airflow is an overkill(though a very reliable and beautiful). For me it was worth the hassle from the beginning. I could not imagine setting a cronjob to handle hundreds of dependent jobs, hourly(which was my case at work). DAGs are also very reusable - I have dozens of clients to handle and each of them has literally almost the same DAG, differing only in parameters and DB connections. I am able to define an abstract DAG and reuse it.
Facebook may soon set a new record, just not the kind it likes to brag about. The social network is facing a multibillion-dollar fine from the Federal Trade Commission over privacy violations, according to a new report in The Washington Post. SEE ALSO: Snopes quits Facebook's fact-checking program The FTC previously confirmed it had opened an investigation into the social network last March, following the Cambridge Analytica debacle. Last month, The Washington Post reported Facebook's potential fine could be "record-setting," and significantly higher than the $22.5 million Google was fined in 2012 -- the current record-holder for biggest FTC fine against a tech company. But now we have an idea just how massive Facebook's fine could be.