TerpreT: A Probabilistic Programming Language for Program Induction · HackerPapers discussions

TerpreT: A Probabilistic Programming Language for Program Induction — mentioned by justinnk

Sun, 26 May 2024 19:46:01 GMT

Thanks! You may find DeepProbLog by Manhaeve et al. interesting, which brings together logic programming, probabilistic programming and gradient descent/neural networks. Also, more generally, I believe in the field of program synthesis there is some research on deriving programs with gradient descent. However, as also pointed out in the comment below, gradient descent may not always be the best approach to such problems (e.g., https://arxiv.org/abs/1608.04428).

Paper and discussion history. A mention is not an endorsement.

TerpreT: A Probabilistic Programming Language for Program Induction — mentioned by mabrocks

Thu, 09 Jun 2022 09:30:29 GMT

If you're interested in these kinds of things, many years ago we created TerpreT (https://arxiv.org/pdf/1608.04428.pdf and https://github.com/51alg/TerpreT) to look into generic program synthesis problems, using a set of very different techniques (gradient descent, ILP, SMT) on different problem settings (turing machines, boolean circuits, LLVM IR-style basic blocks, and straight assembly).

Paper and discussion history. A mention is not an endorsement.

TerpreT: A Probabilistic Programming Language for Program Induction — mentioned by bmc7505

Thu, 30 Sep 2021 19:01:00 GMT

There is a vast chasm of computational complexity between Chess, Go, and protein folding, to program induction. Unlike problems where the configuration space grows exponentially, the space of valid programs is at least super-exponential and depending on the language family, (e.g. context free, context sensitive, recursively enumerable), can often be undecidable. Furthermore, many language induction problems do not have optimal substructure or overlapping subproblems, two important prerequisites for reinforcement learning to work. In these settings, gradient-based heuristics will only get you…

Paper and discussion history. A mention is not an endorsement.

TerpreT: A Probabilistic Programming Language for Program Induction — mentioned by rapidcheckout

Mon, 08 Jan 2018 14:24:50 GMT

> What sort of things have been achieved with machine-learning over algorithms, though? See also this paper for a comparison of programming by example using gradient descent versus more standard alternatives: https://arxiv.org/abs/1608.04428 The main takeaway is that gradient descent is not a silver bullet for searching over program space.

Paper and discussion history. A mention is not an endorsement.

TerpreT: A Probabilistic Programming Language for Program Induction — HN submission

Wed, 17 Aug 2016 08:30:29 GMT

TerpreT: A Probabilistic Programming Language for Program Induction by MSR

2 points; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.