From cbbee18e49d3ae60e0fbb0f308694b8426620695 Mon Sep 17 00:00:00 2001 From: Patrick Simianer
Date: Mon, 5 Sep 2011 20:26:59 +0200
Subject: added READMEs
---
dtrain/README | 39 +++++++++++++++++++++++++++++++++++++++
dtrain/test/EXAMPLE/README | 5 +++++
2 files changed, 44 insertions(+)
create mode 100644 dtrain/README
create mode 100644 dtrain/test/EXAMPLE/README
(limited to 'dtrain')
diff --git a/dtrain/README b/dtrain/README
new file mode 100644
index 00000000..74bac6a0
--- /dev/null
+++ b/dtrain/README
@@ -0,0 +1,39 @@
+NOTES
+ learner gets all used features (binary! and dense (logprob is sum of logprobs!))
+ weights: see decoder/decoder.cc line 548
+ 40k sents, k=100 = ~400M mem, 1 iteration 45min
+ utils/weights.cc: why wv_?
+ FD, Weights::wv_ grow too large, see utils/weights.cc;
+ decoder/hg.h; decoder/scfg_translator.cc; utils/fdict.cc
+
+TODO
+ enable kbest FILTERING (nofiler vs unique)
+ MULTIPARTITE ranking (108010, 1 vs all, cluster modelscore;score)
+ what about RESCORING?
+ REMEMBER kbest (merge) weights?
+ SELECT iteration with highest (real) BLEU?
+ GENERATED data? (multi-task, ability to learn, perfect translation in nbest, at first all modelscore 1)
+ CACHING (ngrams for scoring)
+ hadoop PIPES imlementation
+ SHARED LM?
+ ITERATION variants
+ once -> average
+ shuffle resulting weights
+ weights AVERAGING in reducer (global Ngram counts)
+ BATCH implementation (no update after each Kbest list)
+ SOFIA --eta_type explicit
+ set REFERENCE for cdec (rescoring)?
+ MORE THAN ONE reference for BLEU?
+ kbest NICER (do not iterate twice)!? -> shared_ptr?
+ DO NOT USE Decoder::Decode (input caching as WordID)!?
+ sparse vector instead of vector