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Automatic differentiation in ML: Where we are and where we should be going
[article]
2019
arXiv
pre-print
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We review the current state of automatic differentiation (AD) for array programming in machine learning (ML), including the different approaches such as operator overloading (OO) and source transformation ...
Unlike existing dataflow programming representations in ML frameworks, our IR naturally supports function calls, higher-order functions and recursion, making ML models easier to implement. ...
Early discussions and brainstorming with Olexa Bilaniuk also helped determining the scope and direction of the project. ...
arXiv:1810.11530v2
fatcat:g2chgpagsvhn5daeka26diuwle
From Cleaning before ML to Cleaning for ML
2021
IEEE Data Engineering Bulletin
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Traditional data cleaning focuses on quality issues of a dataset in isolation of the application using the data-Cleaning Before ML-which can be inefficient and, counterintuitively, degrade the application ...
While recent cleaning approaches take into account signals from the ML model, such as the model accuracy, they are still local to a specific model, and do not take into account the entire application's ...
For instance, the user may specify that the total price in January should be 40 instead of 100, or all values in the output are too low. ...
dblp:journals/debu/NeutatzCA021
fatcat:thspsxnq4rdx3psrijelwbg6pq
ML for ML: Learning Cost Semantics by Experiment
[chapter]
2017
Lecture Notes in Computer Science
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The considered resources in the implementation are heap allocations and execution time. ...
The derived cost semantics are combined with RAML, a state-of-the-art system for automatically deriving resource bounds for OCaml programs. ...
S = P j=1 M i=1 T (i,j) − c∈C n (i,j) c T c 2 where T c are the unknowns that need to be learned. ...
doi:10.1007/978-3-662-54577-5_11
fatcat:ndiuvlejgfdzlbe26dqo5eakdi
Transferable Graph Optimizers for ML Compilers
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2010.12438v1 fatcat:ebt3m6m4v5avnasxy6ymol5g2m
Existing learning based approaches in the literature are sample inefficient, tackle a single optimization problem, and do not generalize to unseen graphs making them infeasible to be deployed in practice ...
On a diverse set of representative graphs consisting of up to 80,000 nodes, including Inception-v3, Transformer-XL, and WaveNet, GO achieves on average 21% improvement over human experts and 18% improvement ...
In this paper, we propose an end-to-end deep RL method (GO) for ML compiler graph optimizations where the learned policy is generalizable to new graphs and transferable across multiple tasks. ...
arXiv:2010.12438v2
fatcat:ju26bxgmajbgfa4wtwvgrc6k2a
Non-Oriented MLS Gradient Fields
2013
Computer graphics forum (Print)
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In particular, we show that our novel isotropic linear approximation outperforms its lower-order alternative: surface or image structures are much better preserved, and instabilities are significantly ...
Thanks to its ease of implementation (on both CPU and GPU) and small performance overhead, we believe our approach will find a widespread use in graphics applications, as demonstrated by the variety of ...
The models of figures 12 and 18 are courtesy of the Stanford Computer Graphics Laboratory, and the model of figure 14 is courtesy of the AIM@SHAPE Shape Repository. ...
doi:10.1111/cgf.12164
fatcat:a56z4bsg4re5lfedz3xz77huui
Kafka-ML: connecting the data stream with ML/AI frameworks
[article]
2020
arXiv
pre-print
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In this paper, we proposed Kafka-ML, an open-source framework that enables the management of TensorFlow ML/AI pipelines through data streams (Apache Kafka). ...
Kafka-ML provides an accessible and user-friendly Web User Interface where users can easily define ML models, to then train, evaluate and deploy them for inference. ...
Moreover, high-availability, load-balancing and fault-tolerance may be required in ML/AI mission-critical applications and should be provided in a transparent way to users. ...
arXiv:2006.04105v2
fatcat:mbfukjzkvbfjjod47k4kykarbq
Programming by Examples: PL Meets ML
[chapter]
2017
Lecture Notes in Computer Science
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There are three key components in a PBE system. (i) A search algorithm that can efficiently search for programs that are consistent with the examples provided by the user. ...
PBE systems are already revolutionizing the application domain of data wrangling and are set to significantly impact several other domains including code refactoring. ...
in this article related to using ML techniques for search and ranking. ...
doi:10.1007/978-3-319-71237-6_1
fatcat:nou2fnkpt5elfj3ohaunnfmy7y
Intriguing Properties of Adversarial ML Attacks in the Problem Space
[article]
2020
arXiv
pre-print
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Our results demonstrate that "adversarial-malware as a service" is a realistic threat, as we automatically generate thousands of realistic and inconspicuous adversarial applications at scale, where on ...
Recent research efforts on adversarial ML have investigated problem-space attacks, focusing on the generation of real evasive objects in domains where, unlike images, there is no clear inverse mapping ...
ACKNOWLEDGEMENTS We thank the anonymous reviewers and our shepherd, Nicolas Papernot, for their constructive feedback, as well as Battista Biggio, Konrad Rieck, and Erwin Quiring for feedback on early ...
arXiv:1911.02142v2
fatcat:fioc4k5eczf2toexvneuetxnhi
QML
2009
Proceedings of the 2009 ACM SIGPLAN workshop on ML - ML '09
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Quantified types co-exist with ordinary ML schemes, which are in turn implicitly introduced and eliminated at let-bindings and use sites, respectively. ...
This paper suggests a modest extension of ML with System F types: the heart of the idea is to extend the language of types with unary universal and existential quantifiers. ...
Acknowledgements Thanks to the ML'09 anonymous reviewers for their valuable suggestions on related work, Philip Wadler for reminding us of O'Toole and Gifford's work (16) , and Simon Peyton Jones for ...
doi:10.1145/1596627.1596630
fatcat:ruxpndc3nvfetlkyspuw4wtxca
Ease.ML/Snoopy: Towards Automatic Feasibility Studies for ML via Quantitative Understanding of "Data Quality for ML"
[article]
2022
arXiv
pre-print
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In this paper, we present Snoopy, with the goal of supporting data scientists and machine learning engineers performing a systematic and theoretically founded feasibility study before building ML applications ...
In our experience of working with domain experts who are using today's AutoML systems, a common problem we encountered is what we call "unrealistic expectations" -- when users are facing a very challenging ...
However, in order to apply a BER estimator in a system for a feasibility study in real-world datasets, we need to be able to go beyond uniform noise. ...
arXiv:2010.08410v3
fatcat:yfxpd6o5efd6finrk2rhmvv3iq
The history of Standard ML
2020
Proceedings of the ACM on Programming Languages (PACMPL)
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The use of parametric polymorphism in its type system, together with the automatic inference of such types, has influenced a wide variety of modern languages (where polymorphism is often referred to as ...
properties, and as a guide to łprincipledž language design. 5 LCF/ML Ð The Original ML Embedded in the LCF Theorem Prover We start with a brief look at some programming languages that influenced the design ...
., using an integer where a real is expected) should be easy to support. ...
doi:10.1145/3386336
fatcat:2hrtsaf5azfe3htngsqvxv3kre
ML-based Visualization Recommendation: Learning to Recommend Visualizations from Data
[article]
2020
arXiv
pre-print
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Visualization recommendation seeks to generate, score, and recommend to users useful visualizations automatically, and are fundamentally important for exploring and gaining insights into a new or existing ...
In this work, we propose the first end-to-end ML-based visualization recommendation system that takes as input a large corpus of datasets and visualizations, learns a model based on this data. ...
model M should be able to assign a high score to this visualization and consider it as effective. ...
arXiv:2009.12316v1
fatcat:k3rr5muny5hn3kvrehglnplgra
Democratizing Data Science through Interactive Curation of ML Pipelines
2019
Proceedings of the 2019 International Conference on Management of Data - SIGMOD '19
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Domain experts are often overwhelmed by such complexity, de-facto inhibiting a wider adoption of ML techniques in other fields. ...
In Machine Learning, high-quality results are only attainable via mindful data preprocessing, hyperparameter tuning and model selection. ...
The view of some "purist" is that the input of a NN should be the raw data and that the model -if correctly tuned, for example, by an automatic NN architecture search -should do all the rest. ...
doi:10.1145/3299869.3319863
dblp:conf/sigmod/ShangZBKECBUK19
fatcat:c7pkyoxqvrbvnb4ztl3vuvweim
Looper: An end-to-end ML platform for product decisions
[article]
2022
arXiv
pre-print
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To address shortcomings of prior platforms, we introduce general principles for and the architecture of an ML platform, Looper, with simple APIs for decision-making and feedback collection. ...
We sum up experiences of platform adopters and describe their learning curve. ...
As in medical trials, (1) we need evidence of a positive effect, (2) side-effects should be tolerable, and (3) we should not overlook evidence of side-effects. ...
arXiv:2110.07554v8
fatcat:idoqe2xo2jbbbicqvswhc37zxu
Intriguing Properties of Adversarial ML Attacks in the Problem Space
2020
2020 IEEE Symposium on Security and Privacy (SP)
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And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections. ...
If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. ...
ACKNOWLEDGEMENTS We thank the anonymous reviewers and our shepherd, Nicolas Papernot, for their constructive feedback, as well as Battista Biggio, Konrad Rieck, and Erwin Quiring for feedback on early ...
doi:10.1109/sp40000.2020.00073
dblp:conf/sp/PierazziPCC20
fatcat:mk34n5mqwndexh6irwqmi6fopa
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