13:20

(ML 2.5) Generalizations for trees (CART)

14:06

(ML 2.4) Growing a classification tree (CART)

24:22

(IC 5.14) Finite-precision arithmetic coding - Decoder

17:37

(IC 5.13) Finite-precision arithmetic coding - Encoder

07:52

(IC 5.12) Finite-precision arithmetic coding - Setup

31:37

(IC 5.11) Finite-precision arithmetic coding - Rescaling

24:20

(IC 5.10) Generalizing arithmetic coding to non-i.i.d. models

19:08

(IC 5.9) Computational complexity of arithmetic coding

32:18

(IC 5.8) Near optimality of arithmetic coding

19:37

(IC 5.7) Decoder for arithmetic coding (infinite-precision)

25:03

(IC 5.4) Why the interval needs to be completely contained

16:29

(IC 5.6) Encoder for arithmetic coding (infinite-precision)

23:23

(IC 5.5) Rescaling operations for arithmetic coding

26:58

(IC 5.3) Arithmetic coding - Example #2

29:05

(IC 5.2) Arithmetic coding - Example #1

06:48

(IC 5.1) Arithmetic coding - introduction

23:46

(IC 4.12) Optimality of Huffman codes (part 7) - existence

09:07

(IC 4.13) Not every optimal prefix code is Huffman

14:09

(IC 4.11) Optimality of Huffman codes (part 6) - induction

22:19

(IC 4.10) Optimality of Huffman codes (part 5) - extension lemma

18:18

(IC 4.9) Optimality of Huffman codes (part 4) - extension and contraction

08:01

(IC 4.8) Optimality of Huffman codes (part 3) - sibling codes

21:51

(IC 4.7) Optimality of Huffman codes (part 2) - weak siblings

14:37

(IC 4.6) Optimality of Huffman codes (part 1) - inverse ordering

11:57

(IC 4.5) An issue with Huffman coding

06:32

(IC 4.4) Weighted minimization with Huffman coding

12:23

(IC 4.3) B-ary Huffman codes

13:43

(IC 4.2) Huffman coding - more examples

12:31

(IC 4.1) Huffman coding - introduction and example

15:36

(IC 3.10) Relative entropy as the mismatch inefficiency

15:49

(IC 3.9) Source coding theorem (optimal lossless compression)

08:30

(IC 3.8) Entropy of i.i.d. random variables

13:25

(IC 3.7) Block codes for compression

03:57

(IC 3.6) Example - entropy as a lower bound

13:57

(IC 3.5) Bounds on optimal expected length

01:44

(IC 3.4) Remark - an alternate proof

17:49

(IC 3.3) Entropy as a lower bound on expected length (part 3)

13:06

(IC 3.2) Entropy as a lower bound on expected length (part 2)

15:20

(IC 3.1) Entropy as a lower bound on expected length (part 1)

12:32

(IC 2.11) Kraft-McMillan - proof sketch for (b)

20:53

(IC 2.10) Kraft-McMillan - examples for (b)

18:20

(IC 2.9) Kraft-McMillan - proof of (a)

13:46

(IC 2.8) Kraft-McMillan inequality - statement

13:14

(IC 2.7) Expected codeword length

05:37

(IC 2.6) Prefix codes - remarks and what's next

15:50

(IC 2.5) Prefix codes

16:00

(IC 2.4) Decoding - prefix versus non-prefix

14:37

(IC 2.3) Symbol codes - definition and examples

13:52

(IC 2.2) Symbol codes - terminology and notation

05:28

(IC 2.1) A puzzle on weighing coins

15:46

(IC 1.5) Examples of source-encoder-channel pipelines

18:12

(IC 1.6) A different notion of "information"

12:33

(IC 1.4) Source-channel separation

11:39

(IC 1.2) Applications of Compression codes

29:10

(IC 1.3) Applications of Error-correcting codes

14:40

(IC 1.1) Information theory and Coding - Outline of topics

13:43

(ML 17.5) Importance sampling - introduction

19:27

(ML 19.11) GP regression - model and inference

14:30

(ML 19.10) GP regression - the key step

19:45

(ML 19.9) GP regression - introduction