Learning to rankLearning to rank or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. Training data consists of lists of items with some partial order specified between items in each list. This order is typically induced by giving a numerical or ordinal score or a binary judgment (e.g. "relevant" or "not relevant") for each item.
ConcertA concert is a live music performance in front of an audience. The performance may be by a single musician, sometimes then called a recital, or by a musical ensemble, such as an orchestra, choir, or band. Concerts are held in a wide variety and size of settings, from private houses and small nightclubs, dedicated concert halls, amphitheatres and parks, to large multipurpose buildings, such as arenas and stadiums. Indoor concerts held in the largest venues are sometimes called arena concerts or amphitheatre concerts.
Attention (machine learning)Machine learning-based attention is a mechanism mimicking cognitive attention. It calculates "soft" weights for each word, more precisely for its embedding, in the context window. It can do it either in parallel (such as in transformers) or sequentially (such as recursive neural networks). "Soft" weights can change during each runtime, in contrast to "hard" weights, which are (pre-)trained and fine-tuned and remain frozen afterwards. Multiple attention heads are used in transformer-based large language models.
Steel guitarA steel guitar (kīkākila) is any guitar played while moving a steel bar or similar hard object against plucked strings. The bar itself is called a "steel" and is the source of the name "steel guitar". The instrument differs from a conventional guitar in that it is played without using frets; conceptually, it is somewhat akin to playing a guitar with one finger (the bar). Known for its portamento capabilities, gliding smoothly over every pitch between notes, the instrument can produce a sinuous crying sound and deep vibrato emulating the human singing voice.
Reinforcement learningReinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs from supervised learning in not needing labelled input/output pairs to be presented, and in not needing sub-optimal actions to be explicitly corrected.
Pop musicPop music is a genre of popular music that originated in its modern form during the mid-1950s in the United States and the United Kingdom. During the 1950s and 1960s, pop music encompassed rock and roll and the youth-oriented styles it influenced. Rock and pop music remained roughly synonymous until the late 1960s, after which pop became associated with music that was more commercial, ephemeral, and accessible.
Extreme learning machineExtreme learning machines are feedforward neural networks for classification, regression, clustering, sparse approximation, compression and feature learning with a single layer or multiple layers of hidden nodes, where the parameters of hidden nodes (not just the weights connecting inputs to hidden nodes) need to be tuned. These hidden nodes can be randomly assigned and never updated (i.e. they are random projection but with nonlinear transforms), or can be inherited from their ancestors without being changed.
Active learning (machine learning)Active learning is a special case of machine learning in which a learning algorithm can interactively query a user (or some other information source) to label new data points with the desired outputs. In statistics literature, it is sometimes also called optimal experimental design. The information source is also called teacher or oracle. There are situations in which unlabeled data is abundant but manual labeling is expensive. In such a scenario, learning algorithms can actively query the user/teacher for labels.
Q-learningQ-learning is a model-free reinforcement learning algorithm to learn the value of an action in a particular state. It does not require a model of the environment (hence "model-free"), and it can handle problems with stochastic transitions and rewards without requiring adaptations. For any finite Markov decision process (FMDP), Q-learning finds an optimal policy in the sense of maximizing the expected value of the total reward over any and all successive steps, starting from the current state.
Record producerA record producer is a music recording project's overall supervisor whose responsibilities can involve a range of creative and technical leadership roles. Typically the job involves hands-on oversight of recording sessions: ensuring artists deliver acceptable performances, supervising the technical engineering of the recording, and coordinating the production team and process. The producer's involvement in a musical project can vary in depth and scope. Sometimes in popular genres the producer may create the recording's entire sound and structure.
