scholarly journals Towards Benchmarking Feature Type Inference for AutoML Platforms

Author(s):  
Vraj Shah ◽  
Jonathan Lacanlale ◽  
Premanand Kumar ◽  
Kevin Yang ◽  
Arun Kumar
Keyword(s):  
2011 ◽  
Vol 46 (2) ◽  
pp. 43-52 ◽  
Author(s):  
Arie Middelkoop ◽  
Atze Dijkstra ◽  
S. Doaitse Swierstra

2016 ◽  
Vol 51 (10) ◽  
pp. 781-799 ◽  
Author(s):  
Calvin Loncaric ◽  
Satish Chandra ◽  
Cole Schlesinger ◽  
Manu Sridharan

1993 ◽  
Vol 19 (1-2) ◽  
pp. 87-125
Author(s):  
Paola Giannini ◽  
Furio Honsell ◽  
Simona Ronchi Della Rocca

In this paper we investigate the type inference problem for a large class of type assignment systems for the λ-calculus. This is the problem of determining if a term has a type in a given system. We discuss, in particular, a collection of type assignment systems which correspond to the typed systems of Barendregt’s “cube”. Type dependencies being shown redundant, we focus on the strongest of all, Fω, the type assignment version of the system Fω of Girard. In order to manipulate uniformly type inferences we give a syntax directed presentation of Fω and introduce the notions of scheme and of principal type scheme. Making essential use of them, we succeed in reducing the type inference problem for Fω to a restriction of the higher order semi-unification problem and in showing that the conditional type inference problem for Fω is undecidable. Throughout the paper we call attention to open problems and formulate some conjectures.


2021 ◽  
Vol 5 (POPL) ◽  
pp. 1-31
Author(s):  
Zvonimir Pavlinovic ◽  
Yusen Su ◽  
Thomas Wies
Keyword(s):  

2016 ◽  
Vol 51 (10) ◽  
pp. 410-429 ◽  
Author(s):  
Satish Chandra ◽  
Colin S. Gordon ◽  
Jean-Baptiste Jeannin ◽  
Cole Schlesinger ◽  
Manu Sridharan ◽  
...  
Keyword(s):  

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