- On a recent trip by night-train to Amsterdam, my mind wandered, and it struck me that Knuth might be terribly misleading on the performance of the binary heap, possibly even by an order of magnitude.
- When we zoom in on the left side (figure 2), we see that there is indeed a factor 10 difference in the time the two algorithms take when running under almost total VM pressure: only 8 to 10 pages of the 1,954 pages allocated are in primary memory at the same time.
- If we simulate a mechanical disk by setting the I/O time to a still-optimistic 10 milliseconds instead (figure 4), then B-heap is 10 percent faster as soon as the kernel steals just a single page from our 1,954-page working set and 37 percent faster when four pages are missing.

- The ability to produce accurate and actionable forecasts of communicable disease incidence and transmission across various time scales will facilitate targeted intervention and prevention strategies, such as increases in health care staffing or vector control measures.
- As the NEA’s reservoir of data — the true lifeblood of AI — on dengue incidence trends expands, researchers can feed information through the learning algorithm to refine its accuracy and efficiency, while ultimately improving Singapore’s public health response.
- Researchers from the University of Southern California Viterbi School of Engineering have taken this concept further, developing an algorithm capable of slowing the spread of communicable disease while also accounting for limited resources and population dynamics over time.
- Considering the ballooning costs of care, the continued emergence of new infectious diseases, and the rise of antimicrobial resistance, AI will likely become an indispensable tool for public health policy planning.

- This report compares the performance of three machine learning techniques for spam detection including Random Forest (RF), k-Nearest Neighbours (kNN) and Support Vector Machines (SVM).
- The idea of automatically classifying spam and non-spam emails by applying machine learning methods has been popular in academia and has been a topic of interest for many researchers.
- This comparison is a real-time process, and therefore the main drawback of this approach is that the kNN algorithm must compute the distance and sort all the training data for each prediction, which can be slow if given a large training dataset (James, Witten, Hastie, & Tibshirani, 2013, pp.
- We determine from the results that k-Nearest Neighbours (kNN) and Support Vector Machine (SVM) perform similar weak regarding accuracy and Random Forest (RF) outperforms both.
- Therefore due to its design Random Forest performs relatively well "out-of-the-box" compared to k-Nearest Neighbours and Support Vector Machine.

- This insight suggests that we should dynamically update the low-precision representation: as the gradients get smaller, we should use fixed-point numbers that have a smaller delta and cover a smaller range.
- HALP is our algorithm which runs SVRG and uses bit centering with a full gradient at every epoch to update the low-precision representation.
- First, we showed that for strongly convex, Lipschitz smooth functions (this is the standard setting under which the convergence rate of SVRG was originally analyzed), as long as the number of bits \( b \) we use satisfies \[ 2^b > O\left(\kappa \sqrt{d} \right) \] where \( \kappa \) is the condition number of the problem, then for an appropriate setting of the step size and epoch length (details for how to set these are in the paper), HALP will converge at a linear rate to arbitrarily accurate solutions.

- It’s been almost eight weeks since Facebook revamped its News Feed algorithm, pushing posts from friends and family higher in people’s feeds at the expense of posts from brands and publishers.
- The number of ad impressions Facebook delivered in News Feed in January was down year over year, and in February ad impressions were up, but at a much smaller rate than previous months, according to data from AdStage, an ad tech startup that is one of Facebook’s official marketing partners.
- It marked the two highest year-over-year jumps in ad prices for Facebook over of the past 14 months.
- It’s also early — the data highlights just seven weeks of ad spending since the algorithm change was unveiled.
- Facebook is an ads business so it’s worth watching closely to see how changes to its consumer experience impact its bottom line, or advertisers eager to hand over their money.

- The Stigler diet is an optimization problem named for George Stigler, a 1982 Nobel Laureate in economics, who posed the following problem: For a moderately active man weighing 154 pounds, how much of each of 77 foods should be eaten on a daily basis so that the man’s intake of nine nutrients will be at least equal to the recommended dietary allowances (RDAs) suggested by the National Research Council in 1943, with the cost of the diet being minimal?
- Seven years after Stigler made his initial estimates, the development of George Dantzig's Simplex algorithm made it possible to solve the problem without relying on heuristic methods.
- Dantzig's algorithm describes a method of traversing the vertices of a polytope of N+1 dimensions in order to find the optimal solution to a specific situation.

- Line breaking, also known as word wrapping or paragraph formation, is the problem of dividing a text into a sequence of lines so that every line spans at most some fixed width.
- The method using dynamic programming can be written as two nested loops: the outer one iterates over every word and the inner one searches for the most suitable break.
- Hirschberg and Larmore showed in 1987 an algorithm which is able to use binary search instead of the inner loop in the case the weight function is "concave".
- A concave weight function implies that the matrix is totally monotone and in 1987 Shor, Moran, Aggarwal, Wilber and Klawe devised an algorithm which finds the row maxima of such matrix in linear time.
- A Linear-Time Algorithm for Concave One-Dimensional Dynamic Programming.
- Bridging the Algorithm Gap: A Linear-time Functional Program for Paragraph Formatting.

- The women-focused publisher LittleThings is shutting its doors, in large part due to Facebook's recent move, the company's CEO Joe Spieser told Business Insider.
- But Spieser said that the recent algorithm shift, which Facebook has said was designed to tamp down content that is consumed passively - and would instead focus on posts from people's friends and family - took out roughly 75% of LittleThings' organic traffic, while hammering its profit margins.
- Instead of waiting for the next Facebook newsfeed update, we entered into a sale-process in November that would allow us to merge with a large media entity that could bring our business diversification of both traffic and revenue.
- The businesses looking to acquire LittleThings got spooked and promptly exited the sale process, leaving us in jeopardy of our bank debt convenants and ultimately bringing an expedited end to our incredible story.