Deep Inference 2017


Notes:

  • Learning semantic parsers
  • Semantic deep learning
  • Word rewriting systems

Wikipedia:

See also:

100 Best WolframAlpha VideosDeep Inference 2014


Removing cycles from proofs
A Aler Tubella, A Guglielmi… – LIPIcs-Leibniz International …, 2017 – drops.dagstuhl.de
… Abstract If we track atom occurrences in classical propositional proofs in deep inference, we see that they can form cyclic structures between cuts and identity steps … Keywords and phrases proof theory, deep inference, proof complexity …

Inference in the age of big data: Future perspectives on neuroscience
D Bzdok, BTT Yeo – Neuroimage, 2017 – Elsevier

Deepeye: Resource efficient local execution of multiple deep vision models using wearable commodity hardware
A Mathur, ND Lane, S Bhattacharya, A Boran… – Proceedings of the 15th …, 2017 – dl.acm.org
… 3. MULTIPLE MODEL DEEP INFERENCE PIPELINE In this section we describe the inference pipeline of DeepEye … Figure 5: Overview of the DeepEye Inference Engine Figure 5 illustrates the various components of the deep inference engine …

Deep Inference, Expansion Trees, and Proof Graphs for Second Order Propositional Multiplicative Linear Logic
L Straßburger – 2017 – hal.inria.fr
In this paper we introduce the notion of expansion tree for linear logic. As in Miller’s original work, we have a shallow reading of an expansion tree that corresponds to the conclusion of the proof, and a deep reading which is a formula that can be proved by propositional rules.

Graphical sequent calculi for modal logics
M Ma, AV Pietarinen – arXiv preprint arXiv:1703.02197, 2017 – arxiv.org
… These graphical calculi are of the nature of deep inference … Deep inference systems for modal logics, such as deep sequent calculi developed by Brünnler [7, 8] and Stouppa [22], are also largely syntactic. There exists also deep inference for hybrid logic ([19]) …

Peirce’s sequent proofs of distributivity
M Ma, AV Pietarinen – Indian Conference on Logic and Its Applications, 2017 – Springer
… Peirce’s 1896 system \(\alpha \) has, due to the ‘deep inference’ nature of its proofs, very short proofs of distributivity … The alpha system is essentially a type of deep inference in the sense that inference rules apply inside graphs in the positions …

Surface proofs for nonsymmetric linear logic
L Dunn, J Vicary – arXiv preprint arXiv:1701.04917, 2017 – arxiv.org
… Our approach has a local flavour which is shared by the deep-inference model of proof analysis [8] and the access to monoidal coherence that it allows [9]; however, the coherence property we make use of is strictly more powerful, as it operates in a fragment that combines the …

Subatomic proof systems: Splittable systems
AA Tubella, A Guglielmi – arXiv preprint arXiv:1703.10258, 2017 – arxiv.org
… f . Crucially, in order to define and operate on this new structure, we need to abandon Gentzen formalisms and use deep inference … connectives. The idea behind deep inference is to set proof composition free from the classical logic bias …

Few-Shot Adversarial Domain Adaptation
S Motiian, Q Jones, S Iranmanesh… – Advances in Neural …, 2017 – papers.nips.cc
… The second challenge is addressed by using adversarial learning [18] to train a deep inference function, which confuses a well-trained domain-class discriminator (DCD) while maintaining a high classification accuracy for the source samples …

Combinatorial Flows and Proof Compression
L Straßburger – 2017 – hal.inria.fr
… We show a normalization procedure for combinatorial flows, and how syntactic proofs in sequent calculus, deep inference, and Frege systems are translated into combinatorial flows and vice versa. Key-words: Combinatorial …

Privacy-Preserving Deep Inference for Rich User Data on The Cloud
SA Osia, AS Shamsabadi, A Taheri, K Katevas… – arXiv preprint arXiv …, 2017 – arxiv.org
Abstract: Deep neural networks are increasingly being used in a variety of machine learning applications applied to rich user data on the cloud. However, this approach introduces a number of privacy and efficiency challenges, as the cloud operator can perform secondary

Towards Efficient Deep Inference for Mobile Applications
T Guo – arXiv preprint arXiv:1707.04610, 2017 – arxiv.org
Abstract: Mobile applications are benefiting significantly from the advancement in deep learning, eg providing new features. Given a trained deep learning model, applications usually need to perform a series of matrix operations based on the input data, in order to

AN UNAVOIDABLE CONTRACTION LOOP IN MONOTONE DEEP INFERENCE
A DAS – cs.bath.ac.uk
Recall that this is not derivable in 1s, ml. Indeed there could be no final step (in CoS-style), since any step would break soundness. 1 It remains underivable in the presence of units, since they can only help when there is some triviality around (see [Das13]), which is not the

Subatomic Proof Systems, Coherence Spaces and Post’s Lattice
L Roversi – cs.ox.ac.uk
… Luca Roversi Università di Torino — Dipartimento di Informatica? Deep inference is an approach to structural proof theory which looks at the deductive rules as rewriting rules that can be applied to the formulas of a derivation at any depth of their abstract syntax tree …

Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in Video
MJ Shafiee, B Chywl, F Li, A Wong – arXiv preprint arXiv:1709.05943, 2017 – arxiv.org
… tection performance. Second, a motion-adaptive inference method is introduced into the proposed Fast YOLO framework to reduce the frequency of deep inference with O-YOLOv2 based on tempo- ral motion characteristics. The …

Proof Analysis of Peirce’s Alpha System of Graphs
M Ma, AV Pietarinen – Studia Logica, 2017 – Springer
… Proof Analysis of Peirce’s Alpha System of Graphs Abstract. Charles Peirce’s alpha system S? is reformulated into a deep inference system where the rules are given in terms of deep graphical structures and each rule has its sym- metrical rule in the system …

Deep Active Inference
K Ueltzhöffer – arXiv preprint arXiv:1709.02341, 2017 – arxiv.org
… In short, amortisation enables one to convert a deep inference or deep deconvolution problem into a deep learning problem – by finding a static non-linear mapping between (time varying) inputs and (approximate) posterior beliefs about the states generating those inputs …

Proof Complexity and Proof Compression via Combinatorial Flows
L Straßburger – cs.swansea.ac.uk
… For this, a deep inference proof systems has been used that can speak about cut elimination and extension elimination at the same time so that the two proof compression mechanisms can be studied together … 3. Relation to deep inference proofs …

On the Length of Medial-Switch-Mix Derivations
P Bruscoli, L Straßburger – International Workshop on Logic, Language …, 2017 – Springer
Switch and medial are two inference rules that play a central role in many deep inference proof systems. In specific proof systems, the mix rule may also be present … Abstract. Switch and medial are two inference rules that play a central role in many deep inference proof systems …

Knowledge expression and reasoning model for tomato disease diagnosis
L Yingying, Z Xiaoyan, Z Xiaodong… – … (ICIM), 2017 3rd …, 2017 – ieeexplore.ieee.org
… method of rules and knowledge trees. Based on this hybrid method of knowledge representation we used the forward reasoning and deep inference method to complete tomato disease diagnosis. The expert system adopted the …

Embedded Deep Neural Network Processing: Algorithmic and Processor Techniques Bring Deep Learning to IoT and Edge Devices
M Verhelst, B Moons – IEEE Solid-State Circuits Magazine, 2017 – ieeexplore.ieee.org
… Challenges for Embedded Deep Inference Both the training of a deep network and its own inferences to perform new classifications are now typically executed on power-hungry serv- ers and GPUs [Figure 5(a)]. There is, however, a strong demand to move the inference step, in …

On noncommutative extensions of linear logic
S Slavnov – arXiv preprint arXiv:1703.10092, 2017 – arxiv.org
… Pomset logic is defined by means of proof-nets, later a deep inference system BV [8] was designed for this extension, but equivalence of system has not been proven up to now … Later, a deep inference system BV was designed [8] to capture Pomset logic …

Combinatorial Flows and their Normalisation
L Straßburger – FSCD 2017-2nd International Conference on Formal …, 2017 – hal.inria.fr
… 1998 ACM Subject Classification F.4.1 Mathematical Logic – Proof theory Keywords and phrases proof equivalence, cut elimination, substitution, deep inference Digital Object Identifier 10.4230/LIPIcs.FSCD.2017.31 1 Introduction …

Towards Human-level Machine Reading Comprehension: Reasoning and Inference with Multiple Strategies
Y Xu, J Liu, J Gao, Y Shen, X Liu – arXiv preprint arXiv:1711.04964, 2017 – arxiv.org
Page 1. Towards Human-level Machine Reading Comprehension: Reasoning and Inference with Multiple Strategies Yichong Xu1?, Jingjing Liu2, Jianfeng Gao2, Yelong Shen2, and Xiaodong Liu2 1 Carnegie Mellon University …

Distributed Computing in Social Media Analytics
M Riemer – Distributed Computing in Big Data Analytics, 2017 – Springer
… This type of query of easily accessible with Big Data ready text matching software like SystemT [23], ElasticSearch, or Solr. The most difficult types of user segmentation require deep inference and higher level reasoning about the contents of a user’s post …

Mobile/Embedded DNN and AI SoCs
HJ Yoo – cmu.edu
Page 1. Mobile/Embedded DNN and AI SoCs Hoi-Jun Yoo KAIST Page 2. Outline 1. Deep Neural Network Processor – Mobile DNN Applications – Basic CNN Architectures 2. M/E-DNN: Mobile/Embedded Deep Neural Network – Requirements of M/E-DNN …

SquishedNets: Squishing SqueezeNet further for edge device scenarios via deep evolutionary synthesis
MJ Shafiee, F Li, B Chwyl, A Wong – arXiv preprint arXiv:1711.07459, 2017 – arxiv.org
… point precision to fixed-point precision [12], 2-bit precision [6, 13, 7], or 1-bit precision [1, 8]. While this approach leads to greatly reduced model sizes, the resulting deep neural networks often require spe- cialized hardware support for accelerated deep inference and training on …

Identifying Useful Inference Paths in Large Commonsense Knowledge Bases by Retrograde Analysis
ASKM Goolsbey – 2017 – aaai.org
… to an intermediate state sn. TRule(a) and Substitutions(a) denote the rule and bindings associated with the transfor- mation link a. Cognitive systems often need to make deep inference chains. Let us introduce some notation …

A study of normalisation through subatomic logic
A Aler Tubella – 2017 – opus.bath.ac.uk
… In this thesis, we provide a new approach within the setting of deep inference, which we call subatomic, that allows us to present a wide variety of propositional proof systems in such a way that every rule is an instance of a single linear rule scheme …

Towards Atomic Graphs
DR Sherratt, M Solieri – 2017 – people.bath.ac.uk
… (3) where zi is the subset of z containing all the variables free in ti. This calculus is a Curry-Howard interpretation of a deep inference [4] proof system for intuitionistic logic. In particular, the distributor is the computational interpretation of the distribution rule in this system …

A Heuristic Proof Procedure for First-Order Logic
K Kwon – arXiv preprint arXiv:1712.05665, 2017 – arxiv.org
… In this paper, inspired by the seminal work of [1], we present a variant of LK, called LKg (g for game), which yields a proof in normal form with the following features: • All the quantifier inferences are processed first. This is achieved via deep inference …

Is Free Recall Active: The Testing Effect through the ICAP Lens
C Bruchok, C Mar, SD Craig – Journal of Interactive Learning …, 2017 – learntechlib.org
… heartbeat and the types of circulation. the posttest included 20 open-ended items, five shallow (implicit) and 15 deep (inference), selected from the same source as the text (Chi et al., 2001). explicit questions were not included …

23rd Workshop on Logic, Language, Information and Computation (WoLLIC 2016)
J Väänänen, R Queiroz, MO Galindo… – Logic Journal of the …, 2017 – academic.oup.com
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Accelerating mobile audio sensing algorithms through on-chip gpu offloading
P Georgiev, ND Lane, C Mascolo, D Chu – Proceedings of the 15th …, 2017 – dl.acm.org
… However, there has been little exploration into the performance and energy trade-offs mobile GPUs can deliver for the increasingly popular workload of deep-inference audio sensing tasks, such as, spoken keyword spotting in energy-constrained smartphones and wearables …

Elementary-base cirquent calculus I: Parallel and choice connectives
G Japaridze – arXiv preprint arXiv:1707.04823, 2017 – arxiv.org
… ie moveless, games. MSC: primary: 03B47; secondary: 03B70; 03F03; 03F20; 68T15. Keywords: Proof theory; Cirquent calculus; Resource semantics; Deep inference; Computability logic 1 Introduction Computability logic, or …

Mass Evidence Accumulation and Traveler Risk Scoring Engine in e-Border Infrastructure
K Lai, SC Eastwood, WA Shier… – IEEE Transactions …, 2017 – ieeexplore.ieee.org
… We adapted this methodology, with some modifications, and developed a unified platform for a deep inference based on causal networks, a mechanism of conditional state representation, data structure requirements, and selected metrics of uncertainty …

A uniform framework for substructural logics with modalities
B Lellmann, C Olarte, E Pimentel – LPAR-21, 2017 – sites.google.com
… 2.2 A linear nested sequent system for linear logic In [Str02, GMM98], systems of local rules for linear logic were proposed. While in [Str02] locality was achieved by the use of deep inference [Gug07], in [GMM98] the so called 2-sequents systems were used …

Proof theory for indexed nested sequents
S Marin, L Straßburger – … on Automated Reasoning with Analytic Tableaux …, 2017 – Springer
Fitting’s indexed nested sequents can be used to give deductive systems to modal logics which cannot be captured by pure nested sequents. In this paper we show how the standard cut-elimination procedu.

Deep learning in digital marketing: brand detection and emotion recognition
B Ribeiro, G Oliveira, A Laranjeira… – International Journal of …, 2017 – inderscienceonline.com
Page 1. 32 Int. J. Machine Intelligence and Sensory Signal Processing, Vol. 2, No. 1, 2017 Copyright © 2017 Inderscience Enterprises Ltd. Deep learning in digital marketing: brand detection and emotion recognition Bernardete Ribeiro …

Full Curriculum Vitae
IS Autexier – 2017 – informatik.uni-bremen.de
Page 1. Full Curriculum Vitae Dr.-Ing. Serge Autexier Table of Contents Short Curriculum Vitae . . . . . 1 Summary of Academic Activities . . . . . 5 Research Program . . . . . 14 References . . . . . 26 Educational Activities …

Spectrum inference in cognitive radio networks: Algorithms and applications
G Ding, Y Jiao, J Wang, Y Zou, Q Wu… – … Surveys & Tutorials, 2017 – ieeexplore.ieee.org
… Experimental approaches Spectrum sensing Spectrum decision Spectrum mobility Spectrum sharing Performance limits More applications Cooperative inference Deep inference With spectrum sensing With spectrum database With spectrum map Metrics Fig …

On the proof theory of indexed nested sequents for classical and intuitionistic modal logics
S Marin, L Straßburger – 2017 – hal.inria.fr
Page 1. On the Proof Theory of Indexed Nested Sequents for Classical and Intuitionistic Modal Logics Sonia Marin, Lutz Straßburger To cite this version: Sonia Marin, Lutz Straßburger. On the Proof Theory of Indexed Nested Sequents for Classical and Intuitionistic Modal Logics …

Proof checking and logic programming
D Miller – Formal Aspects of Computing, 2017 – Springer
… Still other structures can be accepted as proofs, such as proof nets, matings, deep inference, and winning strategies. 1 Some specialized theorem provers related to SAT solving have adopted standards of outputting their proof evidence (see, for example, [WHH14]). Page 5 …

Towards a unified complexity theory of total functions
PW Goldberg, CH Papadimitriou – Journal of Computer and System …, 2017 – Elsevier
The class TFNP, of NP search problems where all instances have solutions, appears not to have complete problems. However, TFNP contains various syntactic subcla.

Search for Program Structure
G Scherer – 2nd Summit on Advances in Programming Languages …, 2017 – hal.inria.fr
… of proofs has been studied for a long time by logicians, who proposed many different means of representing a mathematical proof, meant to better capture its identity, to strive at canonicity: natural deduction, sequent calculus, hypersequents / deep inference, focused sequents …

Levels of reading comprehension across text types: A comparison of literal and inferential comprehension of expository and narrative texts in Iranian EFL learners
M Saadatnia, S Ketabi, M Tavakoli – Journal of psycholinguistic research, 2017 – Springer
… coherent mental representation of the text subject. Hence, it can be said that rich and deep inference making relies less on the text itself and more on other mental processes (Alptekin 2006). At the inferential level, the reader …

A Complete Bibliography of ACM Transactions on Computational Logic
NHF Beebe – 2017 – ctan.math.utah.edu
Page 1. A Complete Bibliography of ACM Transactions on Computational Logic Nelson HF Beebe University of Utah Department of Mathematics, 110 LCB 155 S 1400 E RM 233 Salt Lake City, UT 84112-0090 USA Tel: +1 801 581 5254 FAX: +1 801 581 4148 …

Sleep, Psychopathology, and Culture
R Wallace – Computational Psychiatry, 2017 – Springer
… or their generalizations (Cover and Thomas 2006). It is important to note that R(D) is always a convex function of D, ie, a reverse J-shaped curve, allowing deep inference (eg, Ellis 1985). This allows invocation of a dynamic …

On sequents of formulas
A Kornell – arXiv preprint arXiv:1704.08155, 2017 – arxiv.org
… I had obtained the complete list of logical axioms for positivistic proof before I encountered Beklemishev’s work on positive deep inference [2]. The application of positive deep inference to predicate logic may nevertheless be new …

Neural network methods for natural language processing
Y Goldberg – Synthesis Lectures on Human Language …, 2017 – morganclaypool.com
Page 1. GOL DBE R G NEUR AL NE T W OR K ME T HODS FOR N A T UR AL L ANGU A GE P R O CE SSING MOR GAN & CL A YPO OL Page 2. Page 3. Neural Network Methods for Natural Language Processing Page 4. Synthesis Lectures on Human Language Technologies …

An efficient proof-producing framework for formula processing
H Barbosa, JC Blanchette, P Fontaine – 2017 – pdfs.semanticscholar.org
Page 1. An Efficient Proof-Producing Framework for Formula Processing Haniel Barbosa1,2, Jasmin Christian Blanchette3,1,4, and Pascal Fontaine1 1 Inria, Loria, and Université de Lorraine, Nancy, France 2 Universidade Federal …

A Cut-free sequent calculus for modal logic S5
M Aghaei, H Mohammadi – arXiv preprint arXiv:1711.04634, 2017 – arxiv.org
… 2 [6] Torben Braüner. A cut-free Gentzen formulation of the modal logic S5. Logic Journal of IGPL, 8(5):629-643, 2000. 2 [7] Phiniki Stouppa. A deep inference system for the modal logic S5. Studia Logica, 85(2):199-214, 2007. 2 [8] Claudio Cerrato et al …

A Cointuitionistic Adjoint Logic
H Eades III, G Bellin – arXiv preprint arXiv:1708.05896, 2017 – arxiv.org
Page 1. A COINTUITIONISTIC ADJOINT LOGIC HARLEY EADES III AND GIANLUIGI BELLIN e-mail address: heades@augusta.edu Computer Science, Augusta University, Augusta, GA e-mail address: gianluigi.bellin@univr.it …

The structural variability of quarters and residential areas in the historical texture of the city of Yazd based on Islamic rules and jurisprudence: a case study of …
H Azizi Bondarabady… – Journal of Urbanism …, 2017 – Taylor & Francis

Cultural Epigenetics: On the Missing Heritability of Complex Diseases
R Wallace – Computational Psychiatry, 2017 – Springer
We extend a cognitive paradigm for gene expression based on the asymptotic limit theorems of information theory to the epigenetic epidemiology of complex developmental disorders in humans. In particul.

Modularisation of sequent calculi for normal and non-normal modalities
B Lellmann, E Pimentel – arXiv preprint arXiv:1702.08193, 2017 – arxiv.org
… While this is one of the main features of nested sequent calculi and deep inference in general [Guglielmi and Straßburger 2001], ACM Transactions on Computational Logic, Vol. 1, No. 1, Article 1, Publication date: January 2016. Page 4. 1:4 B. Lellmann and E. Pimentel …

Heterogeneous resource mobile sensing: computational offloading, scheduling and algorithm optimisation
P Georgiev – 2017 – cl.cam.ac.uk
… To answer these questions we prototype the design and implementation of audio sensing systems that interleave the execution of multiple concurrent deep-inference pipelines. We introduce optimisations to efficiently leverage the shared use of co-processor and GPU …

Multi-focused cut elimination
T BROCK-NANNESTAD, N GUENOT – Mathematical Structures in …, 2017 – cambridge.org
Page 1. Math. Struct. in Comp. Science: page 1 of 37. c Cambridge University Press 2017 doi:10.1017/S0960129516000451 Multi-focused cut elimination TAUS BROCK-NANNESTAD † and NICOLAS GUENOT ‡ †INRIA Saclay …

Unified correspondence and proof theory for strict implication
M Ma, Z Zhao – Journal of Logic and Computation, 2017 – academic.oup.com
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Assertion and denial: A contribution from logical notations
AV Pietarinen, F Bellucci – Journal of Applied Logic, 2017 – Elsevier
This paper presents two major aspects of Frege’s and Peirce’s views on assertion and denial: first, their arguments for the notational choices concerning the re.

Reprint of: Assertion and denial: A contribution from logical notations
AV Pietarinen, F Bellucci – Journal of Applied Logic, 2017 – Elsevier
This paper presents two major aspects of Frege’s and Peirce’s views on assertion and denial: first, their arguments for the notational choices concerning the re.

Computational Psychiatry
R Wallace, R Wallace – 2017 – Springer
Page 1. Rodrick Wallace Computational Psychiatry A Systems Biology Approach to the Epigenetics of Mental Disorders Page 2. Computational Psychiatry Page 3. Rodrick Wallace Computational Psychiatry A Systems Biology Approach to the Epigenetics of Mental Disorders …

Alternating time bounds from variants of focussed proof systems
A Das – anupamdas.com
… The left-right direction is essentially the correctness of deep inference under positive contexts, whereas the right-left direction follows by substituting A for a. Corollary 28. i ??xA? if and only if i (x ? ?A?) ? (¬x ? ?A?). Proof …

Science and the Truthfulness of Beauty: How the Personal Perspective Discovers Creation
R Gilbert – 2017 – books.google.com
Page 1. Page 2. R SCIENCE AND THE TRUTHEUNESS OF BEAUTY HOW THE PERSONAL PERSPECIVE DISCOVERS CREATION Robert Gilbert R ou I l ; d. GES c n c : A N p RG o N SLR s Page 3. pi Science and the Truthfulness …

Women’s Work: Human Rights Journalism in Chechnya, A Case Study of Anna Politkovskaya
SM Thompson – 2017 – vtechworks.lib.vt.edu
… than that. Whether or not this is simply a reflection of her personal style, or whether she views deep inference based on limited emotional cues as bad journalism, is not clear. What is clear, though, is that this refusal to give into the type of observant psychoanalysis, when it is not …

Sentient Conceptualisations: Feeling for Time in the Sciences of the Past
C Simonetti – 2017 – books.google.com
… at the trowel’s edge 5.2 Edgeworth’s ontology of the trowel 5.3 Plan of a circular arrangement of postholes 5.4 Plan of an area being trowelled 6.1 Retrospective paradox in anthropological writing as anthropologists turn away from the field 6.2 Edgeworth’s deep inference 7.1 De …

The exp-log normal form of types: Decomposing extensional equality and representing terms compactly
D Ilik – ACM SIGPLAN Notices, 2017 – dl.acm.org
Page 1. Co nsistent * Complete * W ellDo cum ente d* Easy to Re use * * E va lu ated * P O P L * Artifact * A E C The exp-log Normal Form of Types Decomposing Extensional Equality and Representing Terms Compactly Danko …

Categories and Modalities
K Kishida – Categories for the Working Philosopher, 2017 – books.google.com
Page 178. 9 Categories and Modalities Kohei Kishida 9.1 Syntax, Semantics, and Duality Category theory provides various guiding principles for modal logic and its semantics. One is the so-called syntax-semantics duality. Stone …

Multicomponent Proof-theoretic Method for Proving Interpolation Properties
R Kuznets – publik.tuwien.ac.at
Page 1. Multicomponent Proof-theoretic Method for Proving Interpolation Properties Roman Kuznets1 Institut für Computersprachen, Technische Universität Wien Abstract Proof-theoretic method has been successfully used almost …