knowledge and strategies from past experience to new experiences, is one of the primary desiderata for models of natural language processing (NLP), as well as for models in the wider field of machine learning1,2. For some, generalization is crucial to ensure that models behave robustly, reliabl...
The term robustness is ubiquitous in modern Machine Learning (ML). However, its meaning varies depending on context and community. Researchers either focus on narrow technical definitions, such as adversarial robustness, natural distribution shifts, and performativity, or they simply leave open what ...
with high probability, a good performance on previously unseen data points. In particular, we provide a precise meaning of "sufficiently large” in terms of properties of the QMLM and the employed training procedure.
Generalizing is finding pattern in order to not overfit. See Evaluation A good generalization helps us to see the meaning of each feature, and puts the whole into a broader perspective.Terry Gannon Documentation / Reference wiki/Overfitting Introduction to Data Science - University of Washingto...
stationarity:A property of data in a data set, in which the data distributionstays constantacross one or more dimensions. Most commonly, that dimension istime, meaning that data exhibiting stationarity doesn't change over time. For example, data that exhibits stationaritydoesn't changefrom September...
Language learning as uncertainty reduction: The role of prediction error in linguistic generalization and item-learning Maša VujovićMichael RamscarElizabeth Wonnacott Aug 2021 Abstract Discriminative theories frame language learning as a process of reducing uncertainty about the meaning of an utterance ...
Systematic generalization is the ability to combine known parts into novel meaning; an important aspect of efficient human learning, but a weakness of neur... L Ruis,B Lake 被引量: 0发表: 2022年 A non-intrusive speech quality evaluation algorithm combining auxiliary target learning and convolution...
On account of the meaning of the particle only, we can see that it is also one of the two readings of the statement: In what is alike, there is only the presence [of the reason] where the particle only is inserted into the predicate position. n⋅nāga eliminates this unwanted ...
This decomposition is the most meaning- ful when its components are nonnegative. In general, e1, e2, and e3 can be negative, for example when samples of testing domains are significantly easier to classify compared to those of training domains. However, this is a rare phenomenon and ...
in bothaandb) was the most common output for both people and MLC, translating the queries in a one-to-one (1-to-1) and left-to-right manner consistent with iconic concatenation (IC). The rightmost patterns (in bothaandb) are less clearly structured but still generate a unique meaning ...