[PDF] Top 20 Towards structured output prediction of enzyme function
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Towards structured output prediction of enzyme function
... predicting enzyme EC classification we obtain over 85% accuracy (predicting the four digit EC code) and over 91% microlabel F1 score (predicting individual EC ...Standard enzyme families, we obtain over 79% ... See full document
10
Input Output Kernel Regression: Supervised and Semi-Supervised Structured Output Prediction with Operator-Valued Kernels
... Input Output Kernel Regression (IOKR), a novel class of penalized regression problems based on the definition of an output scalar-valued kernel and an input operator- valued ...of structured ... See full document
48
Structured Sparsity in Structured Prediction
... for structured outputs are in demand across natural language processing, with applications in in- formation extraction, parsing, and machine transla- ...2001), structured support vector machines (Altun et ... See full document
12
StructED: Risk Minimization in Structured Prediction
... a structured prediction task involves defining a set of feature ...the prediction is performed by finding the output label that max- imizes the weighted sum of those feature functions ... See full document
5
Stability and Generalization in Structured Prediction
... From a certain perspective, our work fits into a large body of literature on learning from various types of interdependent data. Most of this is devoted to “unstructured” prediction. Usunier et al. (2006) and ... See full document
52
A Study of Latent Structured Prediction Approaches to Passage Reranking
... the structured output learning framework to represent a ranking as a structured object, with re- spect to which it is possible to directly optimize a ranking ... See full document
11
Benchmarking Approximate Inference Methods for Neural Structured Prediction
... Exact structured inference with neural net- work scoring functions is computationally challenging but several methods have been proposed for approximating ...the output structure di- rectly (Belanger and ... See full document
12
Magic Moments for Structured Output Prediction
... objective function for a learning ...the output space. We show that the Z-score is a convex cost function, such that it can be optimized ...(structured output discriminant analysis) ... See full document
44
Structured Prediction with Output Embeddings for Semantic Image Annotation
... as structured prediction tasks where the goal is to learn functions that map inputs to struc- tured outputs such as sequences, trees or general ...the output is a labeled graph, each node of the ... See full document
6
Structured Prediction via Output Space Search
... constructs structured outputs based on a series of discrete ...given structured-prediction problem by defining an appropriate primitive search space over the possible sequences of ...a ... See full document
34
On Amortizing Inference Cost for Structured Prediction
... part of speech example, we showed redundancy of structures at the sentence level (Figure 2a). How- ever, for part-of-speech tagging, the decisions are rarely, if at all, dependent on a very large context. One direction ... See full document
11
On the World Productivity Distribution: Recent Convergence and Divergence Patterns
... Before going over the results let us recall the differences and complementarities between the deterministic approach used in Section 3 and the stochastic approach of this section. First, in the previous section, I ... See full document
29
THE STRUCTURED MODEL FOR FUNCTION ALLOCATION ANALYSIS
... For the human factor and ergonomics, the Function Allocation was treated consistently as important research theme for half a century[Cummings (2014)]. Historically, the area has focused predominantly on the ... See full document
15
pystruct - Learning Structured Prediction in Python
... PyStruct aims at providing a high-quality implementation with an easy-to-use inter- face, in the high-level Python language. This allows practitioners to efficiently test a range of models, as well as allowing ... See full document
6
Learning Ensembles of Structured Prediction Rules
... tions 2j −1 and 2j with probability 0.97 and other positions with probability 0.5. We forced experts to make similar mistakes by making them select an adjacent alphabet symbol in case of an error. For example, when a ... See full document
12
Multiclass analysis and prediction with network structured covariates
... In contemporary statistical inference and machine learning theory, classification and prediction are of great importance and many approaches have been proposed. Those methods typically include the support vector ... See full document
25
Enabling More Accurate and Efficient Structured Prediction
... in structured models at test-time. We first learn a prediction model that is trained to use subsets of features computed sparsely across the structure of the input; we then use reinforcement learning to ... See full document
131
Sequence based Structured Prediction for Semantic Parsing
... sequence prediction in NLP applications such as machine translation (Sutskever et ...a structured object, namely a logical form that is tree-like by nature and also has to respect cer- tain a priori ... See full document
10
Distilling Knowledge for Search based Structured Prediction
... Search-based structured prediction models the generation of natural language structure (part-of- speech tags, syntax tree, translations, semantic graphs, ... See full document
10
Enzyme function and its evolution
... 33]. Prediction of protein function on a large scale remains a significant ...of function to novel genes and proteins needs to be an automatic ...predicting function, based on the same ... See full document
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