CONCH BUNNIES' PRICKLY HEDGES MADE THE LEAP OF FAITH INTO THE SUBSEQUENT ENTRY

GONNA TWIST THIS ONE THEN STILETTO IT
ALL THESE TINGS HAPPENIN AT ONCE. WHAT A WORLD.

SOME SIMULTANEITY

As a grumbling but happy French comedian
shoves his fingers into the fountain in Dijon,
a troop of monkeys rounds
the horizon of the pink square.
Intent on mischief, they piss in the pool.

After sunning herself on a carpet of chilly blues,
an elderly farmer sneezes theatrically
and feels her abdominal muscles
tighten.

On a country lane in Wiltshire, a mother presses
her sons into a prickly hedge
as a vintage Wolsley speeds
past them in the late afternoon haze.

It rains on the outskirts of Brussels. Koen scrubs mussels
in his bedsit above the bar
on the corner of Avenue Constant Permeke
and Rue Fernand Léger.
It’s five thirty-seven and he still needs to buy beer.

Conch bunny

I bit the head off a chocolate bunny and blew into the hole, producing a sound like wind in a conch. This brought to mind a hotel on a steep hill by the seaside, tractor tyres rolling down the lawn to crash into prickly hedges as dusk began its onset.

Adrew

I need to create something for the Dubdichters Festival.

On the poster, they missed the 'n' out of my name.

Maybe that could be a starting point for a beautiful poem or profound relationship between audience and poet.

a poem containing symbols as well as words

≈ΘŽǾ≤№™₫⁄®¬¬«¶¦§µ§¨

and photos

oo

a poem, all of whose words contain the 'oo' sound in the word 'moon'

gs

Bias-Variance Analysis


Let X be a poem of objects and let dogs bark
and warm spring winds blow cheeks red
distribution (or density) on X × R
(where R reperesents an arbitrary trail of gold.

In other worlds X is a probability density on
pairs hx, yi with x 2 sequence of deduced conclusions and y 2 R.

We now consider an arbitrary space of
insisted joy functions fw : X ! R with w 2 RD.

For example, we might have
fw(x) = w · _(x) where _ : X ! R is a feature map.

But we might also have some other arbitrary function
such as the following “neural network”.

The full bias-variance analysis is to rewrite L2(A) as follows.
L2(A) = ED__N,hx, yi__
_
(fA(D)(x) − y)2_
= ED__N,hx, yi__
_
((fA(D)(x) − fA(x)) − (y − fA(x)))2_
= ED__N,hx, yi__
_
(fA(D)(x) − fA(x))2 − 2(fA(D)(x) − fA(x))(y − fA(x)) + (y − fA(x))2_
= Ex__
_
(fA(D)(x) − fA(x))2_
−2Ehx, yi__
_
(y − fA(x))ED__N
_
fA(D)(x) − fA(x)
__
+Ehx, yi__
_
(y − fA(x))2_
= Ex__
_
(fA(D)(x) − fA(x))2_
+ L2(fA)
= Ex__,D__N
_
(fA(D)(x) − fA(x))2_
+Ex__
_
(fA(x) − f_(x))2_
+Ehx, yi__ genre
_
(y − f_(x))2_
(don't!!)