Search

Search Funnelback University

Search powered by Funnelback
1 - 10 of 35 search results for KA :PC53 |u:mlg.eng.cam.ac.uk where 0 match all words and 35 match some words.
  1. Results that match 1 of 2 words

  2. Data-Efficient Reinforcement Learning inContinuous State-Action…

    https://mlg.eng.cam.ac.uk/pub/pdf/McaRas17.pdf
    13 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. ′,
  3. The Geometry of Random Features Krzysztof Choromanski∗1 Mark…

    https://mlg.eng.cam.ac.uk/adrian/geometry.pdf
    6 May 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
  4. 27 Jan 2023: ¢#£!àÙÃᥠ« {?¥Ñ¥ « £Ñ¥=$ÍѪ «,« ¤ ¥¥¥ « ¤ « « - ¤ K« X ,« ¤Z ¥ ã éå ,-Êã Kå « {ÃÅÑ¥ « ¤Z ,« « £=' , ¥ ,-ª$, 9¤ O+ ª$Ñ¥{%¢]{ÃÅÑ¥ « ¤Z ,« « £#' , Ѫ «
  5. 13 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.
  6. gppl.dvi

    https://mlg.eng.cam.ac.uk/zoubin/papers/icml05chuwei-pl.pdf
    27 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
  7. PILCO: A Model-Based and Data-Efficient Approach to Policy Search

    https://mlg.eng.cam.ac.uk/pub/pdf/DeiRas11.pdf
    13 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.
  8. 27 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
  9. Determinantal Clustering Process - A Nonparametric BayesianApproach…

    https://mlg.eng.cam.ac.uk/pub/pdf/ShaGha13a.pdf
    13 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}.
  10. Scalable Gaussian Process Structured Prediction for Grid Factor Graph …

    https://mlg.eng.cam.ac.uk/pub/pdf/BraQuaNowGha14.pdf
    13 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).
  11. standalone.dvi

    https://mlg.eng.cam.ac.uk/pub/pdf/QuiRasWil07.pdf
    13 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.

Search history

Recently clicked results

Recently clicked results

Your click history is empty.

Recent searches

Recent searches

Your search history is empty.