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Data-Efficient Reinforcement Learning inContinuous State-Action…
https://mlg.eng.cam.ac.uk/pub/pdf/McaRas17.pdf13 Feb 2023: l. 2a,DF ]), and signal variance s. 2a:. ka(x̃i, x̃j) = s2a exp. ( ... where the E squared exponential covariance functions are. ka(x,x′) = s2aq(x,x. ′, -
The Geometry of Random Features Krzysztof Choromanski∗1 Mark…
https://mlg.eng.cam.ac.uk/adrian/geometry.pdf19 Jun 2024: The Geometry of Random Features. Krzysztof Choromanski1 Mark Rowland2 Tamas Sarlos1 Vikas Sindhwani1 Richard E. Turner2 Adrian Weller231Google Brain, NY 2University of Cambridge, UK 3The Alan Turing Institute, UK. Abstract. We present an in-depth -
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https://mlg.eng.cam.ac.uk/zoubin/papers/review.pdf27 Jan 2023: ¢#£!àÙÃᥠ« {?¥Ñ¥ « £Ñ¥=$ÍѪ «,« ¤ ¥¥¥ « ¤ « « - ¤ K« X ,« ¤Z ¥ ã éå ,-Êã Kå « {ÃÅÑ¥ « ¤Z ,« « £=' , ¥ ,-ª$, 9¤ O+ ª$Ñ¥{%¢]{ÃÅÑ¥ « ¤Z ,« « £#' , Ѫ « -
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https://mlg.eng.cam.ac.uk/pub/pdf/GoeRasToletal04.pdf13 Feb 2023: PYáN247L,I <7=Ka 246 2UI > I > 573T3 ã D < 6NL.246 abN= LL,I a L áI? ... DFE MÛUØUZJLNYZMSM 62TJ;á <7=Ka 5X6 a 24II > LÒ246 > Im246 VGM 24IÌà bN<Y< Im246. -
gppl.dvi
https://mlg.eng.cam.ac.uk/zoubin/papers/icml05chuwei-pl.pdf27 Jan 2023: ǩt = [Ka(xt, x1), Ka(xt, x2),. , Ka(xt, xn)].5 Themean of the predictive distribution P(fa(xt)|E, θ) canbe approximated as E[fa(xt)] = ǩtβa where βa is -
PILCO: A Model-Based and Data-Efficient Approach to Policy Search
https://mlg.eng.cam.ac.uk/pub/pdf/DeiRas11.pdf13 Feb 2023: qai =. ka(x̃i, x̃t1)N. (x̃t1 | µ̃t1, Σ̃t1. )dx̃t1. =α2a. |Σ̃t1Λ1a I|exp. ( ... Qij =ka(x̃i,µ̃t1)kb(x̃j,µ̃t1). |R|exp. (12 z>ijR1Σ̃t1zij. )(22). where we defined R := Σ̃t1(Λ1a Λ. -
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https://mlg.eng.cam.ac.uk/zoubin/course04/PCA.pdf27 Jan 2023: "$#. %'&)(,.-0/21435768(9&)(9:;14<=&?>A@CBD68E14GFD:HBI<7FDBKJC<8:;(L 14<7M814<N BD>;>H:;<7OQPO.&)(,.-4RS67FD>TRU&)F?RS67VW X ZY8 = '[AY=] _baTcedgfih]jgkflfnmAopmqdrjUjfsaltvuxwzyZ{xuxoGjUf|}{ZmqcedghcbaTceo{)foGTIoGukvux{IykldUkejrofkToh]{IDaTdUDtv -
Determinantal Clustering Process - A Nonparametric BayesianApproach…
https://mlg.eng.cam.ac.uk/pub/pdf/ShaGha13a.pdf13 Feb 2023: K1A{x} =. (U VV T 1w. ),. where. w = K{x} K{x},AK1A KA,{x},. ... U = K1A 1. wK1A KA,{x}K{x},AK. 1A ,. V = 1wK1A KA,{x}. -
Scalable Gaussian Process Structured Prediction for Grid Factor Graph …
https://mlg.eng.cam.ac.uk/pub/pdf/BraQuaNowGha14.pdf13 Feb 2023: Cov(Ea(xi,yi),Ea(x′i,y′i)) = ka((xi,yi),(x. ′i,y′i)). Cov(Eb(yi,y′′i ),Eb(y. ′i,y′′′i )) = kb((y,y. ′′),(y′,y′′′)). ... We use ka(, ) and kb(, ) to denote a positive definite ker-nel function (Schölkopf & Smola, 2001). -
standalone.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/QuiRasWil07.pdf13 Feb 2023: where we have introduced the shorthand notation4 Qa,b , Ka,uK1u,uKu,b. We. ... For FITC see Remark 7. Recall that we have definedQa,b , Ka,uK. -
Analytic Moment-based Gaussian Process Filtering Marc Peter…
https://mlg.eng.cam.ac.uk/pub/pdf/DeiHubHan09.pdf13 Feb 2023: Analytic Moment-based Gaussian Process Filtering. Marc Peter Deisenroth mpd37@cam.ac.ukComputational and Biological Learning Lab (CBL), University of Cambridge, UKIntelligent Sensor-Actuator-Systems Laboratory (ISAS), Universität Karlsruhe (TH), -
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https://mlg.eng.cam.ac.uk/zoubin/course03/PCA.pdf27 Jan 2023: "$#. %'&)(,.-0/21435768(9&)(9:;14<=&?>A@CBD68E14GFD:HBI<7FDBKJC<8:;(L 14<7M814<N BD>;>H:;<7OQPO.&)(,.-4RS67FD>TRU&)F?RS67VW X ZY8 = '[AY=] _baTcedgfih]jgkflfnmAopmqdrjUjfsaltvuxwzyZ{xuxoGjUf|}{ZmqcedghcbaTceo{)foGTIoGukvux{IykldUkejrofkToh]{IDaTdUDtv -
Non-parametric Bayesian Methods Uncertainty in Artificial…
https://mlg.eng.cam.ac.uk/zoubin/talks/uai05tutorial-b.pdf27 Jan 2023: βk Beta(1 a, b ka). Note: mean of a Beta(a, b) is a/(a b). -
The EM-EP Algorithm forGaussian Process Classification Hyun-Chul Kim� …
https://mlg.eng.cam.ac.uk/zoubin/papers/ecml03.pdf27 Jan 2023: The EM-EP Algorithm forGaussian Process Classification. Hyun-Chul Kim. and Zoubin Ghahramani. Gatsby Computational Neuroscience Unit, UCL,London, WC1N 3AR, UK,. hckim,zoubin @gatsby.ucl.ac.uk,http://www.gatsby.ucl.ac.uk. Abstract. Gaussian process -
Statistical Models for Partial Membership Katherine A. Heller…
https://mlg.eng.cam.ac.uk/pub/pdf/HelWilGha08.pdf13 Feb 2023: W. A). Ken. nedy. (D. M. A). Aka. ka (. D. -
Bayesian Learning forData-Efficient Control Rowan McAllister…
https://mlg.eng.cam.ac.uk/pub/pdf/Mca16.pdf13 Feb 2023: Bayesian Learning forData-Efficient Control. Rowan McAllister. Supervisor: Prof. C.E. Rasmussen. Advisor: Prof. Z. Ghahramani. Department of EngineeringUniversity of Cambridge. This dissertation is submitted for the degree ofDoctor of Philosophy. -
Statistical Models for Partial Membership Katherine A. Heller…
https://mlg.eng.cam.ac.uk/zoubin/papers/HelWilGha08.pdf27 Jan 2023: W. A). Ken. nedy. (D. M. A). Aka. ka (. D. -
1 Robust Filtering and Smoothing with Gaussian Processes Marc ...
https://mlg.eng.cam.ac.uk/pub/pdf/DeiTurHubetal12.pdf13 Feb 2023: With βxa =(Ka σ. 2wa I). 1ya and mfa (xt1) = kfa (X, xt1)>βxa, we obtain. -
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https://mlg.eng.cam.ac.uk/zoubin/papers/lds.pdf27 Jan 2023: "$#%&%&')(,.-%. /102 35476987:<; =4?>A@$:<BDCFE0EAGH02I0B$:. JHKMLONQPMRTSAUWVMLHXZY.R[?]_T7acb?SY7dfegX.hTijeahegX7klnmOo'p'qTrsutwvyxMzQo mOo {|tw}mc1 zQ'twp{}M }Q{|o. }M{|c'p{|orsutcwntw}MMtc}y zM}7Zzmcc?tw}MMtw}s cn }Q{|o n{|}MwMtcv. o'twq? -
1471-2105-10-242.fm
https://mlg.eng.cam.ac.uk/pub/pdf/SavHelXuetal09.pdf13 Feb 2023: IEEE/ACM Transactions on Computa-tional Biology and Bioinformatics 2007 [http://doi.ieeecomputersociety.org/10.1109/TCBB.2007.70269]. 19. Heller KA, Ghahramani Z: Bayesian Hierarchical Clustering.Twenty-second International Conference -
PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos
https://mlg.eng.cam.ac.uk/pub/pdf/ParRasPetDoy18.pdf13 Feb 2023: We use a squared exponential covari-ance function ka(x̃, x̃′) = s2a exp((x̃x̃′)T Λ1a (x̃x̃′)),where sa and Λ = diag([la1, la2,. , -
Perfusion Quantification Using Gaussian ProcessDeconvolution I.K.…
https://mlg.eng.cam.ac.uk/pub/pdf/AndSzyRasetal02.pdf13 Feb 2023: J Magn Reson Imaging 2000;12:381–387. 7. Rempp KA, Brix G, Wenz F, Becker CR, Guckel F, Lorenz WJ. -
Generalization to Local Remappings of the VisuomotorCoordinate…
https://mlg.eng.cam.ac.uk/zoubin/papers/genJN.pdf27 Jan 2023: Generalization to Local Remappings of the VisuomotorCoordinate Transformation. Zoubin Ghahramani,1 Daniel M. Wolpert,2 and Michael I. Jordan1. 1Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, -
psb04.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/DubHwaRan04a.pdf13 Feb 2023: XÄXºÑ«_X_D ArHgÐ6Ñ rQ|O DOrÀ$_µD/76A;È»IJ7&K«_e¿OXD«_ª8-A;ÃjrrªÉ_µ 5 " )OÃjrrª9Dj_ÎÉ»«_Ç;ª|D@j¿DÀ "/D«__r87&ªªX«Q;DÀ_ _ -
psb04.dvi
https://mlg.eng.cam.ac.uk/pub/pdf/DubHwaRanetal04.pdf13 Feb 2023: XÄXºÑ«_X_D ArHgÐ6Ñ rQ|O DOrÀ$_µD/76A;È»IJ7&K«_e¿OXD«_ª8-A;ÃjrrªÉ_µ 5 " )OÃjrrª9Dj_ÎÉ»«_Ç;ª|D@j¿DÀ "/D«__r87&ªªX«Q;DÀ_ _ -
Gaussian Processes forState Space Models andChange Point Detection…
https://mlg.eng.cam.ac.uk/pub/pdf/Tur11.pdf13 Feb 2023: Gaussian Processes forState Space Models andChange Point Detection. Ryan Darby Turner. Department of Engineering. University of Cambridge. A thesis submitted for the degree of. Doctor of Philosophy. July 17, 2011. b. Acknowledgements. I would like -
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https://mlg.eng.cam.ac.uk/zoubin/papers/nlds_preprint.pdf27 Jan 2023: "# $% #&'() ,-$ '.$0/1,324 2. 5&6708:9<;>=@?BA@CED9GFIHJ?LKMONP6NJQR67S6KJ? TPUWVYX[Z]_X[acb!dfehgjiRkhlnmodqp:r@isktdRu'vWiwuyxwz{l|iwr}ziz@d>ehgji<u|dR itvlyqxhuzpr@diwxovu|dvWz{lyqpszlnr@Ez{@dxhro@r@isreoptgjp>d_zjdg{vpromhl|m@modRr:vzpszjdvEitpqr -
http://ijr.sagepub.com/Robotics Research The International Journal of …
https://mlg.eng.cam.ac.uk/pub/pdf/BouAllKre04a.pdf13 Feb 2023: http://ijr.sagepub.com/Robotics Research. The International Journal of. http://ijr.sagepub.com/content/23/7-8/693The online version of this article can be found at:. DOI: 10.1177/0278364904045479. 2004 23: 693The International Journal of Robotics -
http://ijr.sagepub.com/Robotics Research The International Journal of …
https://mlg.eng.cam.ac.uk/pub/pdf/ThrLiuKol04a.pdf13 Feb 2023: http://ijr.sagepub.com/Robotics Research. The International Journal of. http://ijr.sagepub.com/content/23/7-8/693The online version of this article can be found at:. DOI: 10.1177/0278364904045479. 2004 23: 693The International Journal of Robotics -
propagate.dvi
https://mlg.eng.cam.ac.uk/zoubin/papers/CMU-CALD-02-107.pdf27 Jan 2023: #"$&%')( %-,.& /0-123&%-. 4576'8:9;5=<>?A@ >8B@DC5=<EF?G6'?DHI6'JK6-<D5L'@D<DM0N'OBOBN. PRQTSVUPXWYZ2U[]U;_[B. acbed:fgfihjfikGlfnmopcq!r;sXacbturwv-brlx_sv:rwyntzr {Fr;hzhufiv}|3v:tuir;s!tzq+ tq!q!:p:syidA jicI. Dw;_. rtzvgnr;q!tuynxqr q!d:rp!r2fikp -
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https://mlg.eng.cam.ac.uk/zoubin/papers/compmod.pdf27 Jan 2023: "# "$%& (')" &. ,(-. 0/21436587958:;7(<7(1/>=?7(1/@BA CEDGFHIA J&@K:MLNCO/2PQ587 @MA)R0DTS(:;U(7(1IV. W2XZY[][0_a%bdcMeeGcQXfag[ih9cMXj%klmXnpol&qrnpfes[ tvuIwpx y>zp{|}%Ks%%0&K 0KKQxi%%%|&K|QxK;B![GeonpbficM(%bo0! KmcMXf (s¡K¡%[. -
Scalable Inference for StructuredGaussian Process Models Yunus…
https://mlg.eng.cam.ac.uk/pub/pdf/Saa11.pdf13 Feb 2023: namely that if:. p. ([a. b. ])= N. ([µa. µb. ],. [Ka,a Ka,b. Kb,a Kb,b. ]), (1.17). then the means and covariances of marginals are simply the relevant subvectors ... and. submatrices of the joint mean and covariance respectively, i.e., p(a) = N(µa, Ka -
Efficient Reinforcement Learning using Gaussian Processes
https://mlg.eng.cam.ac.uk/pub/pdf/Dei10.pdf13 Feb 2023: Faculty of InformaticsInstitute for AnthropomaticsIntelligent Sensor-Actuator-Systems Laboratory (ISAS)Prof. Dr.-Ing. Uwe D. Hanebeck Sensor-Actuator-Systems. Intelligent. Efficient Reinforcement Learningusing Gaussian Processes. Marc Peter -
Bayesian Time Series Learning with Gaussian Processes Roger…
https://mlg.eng.cam.ac.uk/pub/pdf/Fri15.pdf13 Feb 2023: Bayesian Time Series Learning. with Gaussian Processes. Roger Frigola-AlcaldeDepartment of Engineering. St Edmund’s CollegeUniversity of Cambridge. August 2015. This dissertation is submitted for the degree ofDoctor of Philosophy. SUMMARY. The -
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https://mlg.eng.cam.ac.uk/zoubin/papers/ijprai.pdf27 Jan 2023: "# %$&' )(,-/.012)34,6578:9; #"<. =?>A@ BDCFEHGJI8KLIDM4KLNOKLEDCGPK:Q4R4BTSHU2>ANWVD@ QXK:QXCY>AE8KLZ?[]@ M4>AR_]CFED]baE CYQ. acEDCYdL]M4R_CYQSHU2>LZFZFeAPf%>AEDgD>LEf%>AEDg >AEihjUkl[nmLoprq8sEDeLZtKLEDg. u3vvTw<x4yy{zzz<|}Lv||! |8yL8)yD3) T} Lvl2
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