Vladimir Vovk

Volodya Vovk, V. G. Vovk

2008
78	EE	Vladimir Vovk, Fedor Zhdanov: Prediction with expert advice for the Brier game. ICML 2008: 1104-1111
77	EE	Vladimir Vovk, Glenn Shafer: The game-theoretic capital asset pricing model. Int. J. Approx. Reasoning 49(1): 175-197 (2008)
2007
76	EE	Yuri Kalnishkan, Vladimir Vovk, Michael V. Vyugin: Generalised Entropy and Asymptotic Complexities of Languages. COLT 2007: 293-307
75	EE	Vladimir Vovk: Competing with Stationary Prediction Strategies. COLT 2007: 439-453
74	EE	Harris Papadopoulos, Volodya Vovk, Alex Gammermam: Conformal Prediction with Neural Networks. ICTAI (2) 2007: 388-395
73	EE	Glenn Shafer, Vladimir Vovk: A tutorial on conformal prediction CoRR abs/0706.3188: (2007)
72	EE	Vladimir Vovk: Defensive forecasting for optimal prediction with expert advice CoRR abs/0708.1503: (2007)
71	EE	Vladimir Vovk: Continuous and randomized defensive forecasting: unified view CoRR abs/0708.2353: (2007)
70	EE	Vladimir Vovk: Prediction with expert advice for the Brier game CoRR abs/0710.0485: (2007)
69	EE	Alexander Gammerman, Vladimir Vovk: Hedging Predictions in Machine Learning: The Second Computer Journal Lecture. Comput. J. 50(2): 151-163 (2007)
68	EE	Alexander Gammerman, Vladimir Vovk: Rejoinder Hedging Predictions in Machine Learning. Comput. J. 50(2): 173-177 (2007)
67	EE	Vladimir Vovk: Competing with wild prediction rules. Machine Learning 69(2-3): 193-212 (2007)
66	EE	Vladimir Vovk: Non-asymptotic calibration and resolution. Theor. Comput. Sci. 387(1): 77-89 (2007)
2006
65	EE	Vladimir Vovk: Leading Strategies in Competitive On-Line Prediction. ALT 2006: 214-228
64	EE	Vladimir Vovk: Predictions as Statements and Decisions. COLT 2006: 4
63	EE	Vladimir Vovk: Competing with Wild Prediction Rules. COLT 2006: 559-573
62	EE	Vladimir Vovk: On-Line Regression Competitive with Reproducing Kernel Hilbert Spaces. TAMC 2006: 452-463
61	EE	Vladimir Vovk: Predictions as statements and decisions CoRR abs/cs/0606093: (2006)
60	EE	Vladimir Vovk: Competing with stationary prediction strategies CoRR abs/cs/0607067: (2006)
59	EE	Vladimir Vovk: Leading strategies in competitive on-line prediction CoRR abs/cs/0607134: (2006)
58	EE	Vladimir Vovk: Competing with Markov prediction strategies CoRR abs/cs/0607136: (2006)
57	EE	Vladimir Vovk: Metric entropy in competitive on-line prediction CoRR abs/cs/0609045: (2006)
56	EE	Alexander Gammerman, Vladimir Vovk: Hedging predictions in machine learning CoRR abs/cs/0611011: (2006)
55	EE	Vladimir Vovk: Well-calibrated predictions from on-line compression models. Theor. Comput. Sci. 364(1): 10-26 (2006)
54	EE	Ilia Nouretdinov, Vladimir Vovk: Criterion of calibration for transductive confidence machine with limited feedback. Theor. Comput. Sci. 364(1): 3-9 (2006)
2005
53	EE	Vladimir Vovk: Non-asymptotic Calibration and Resolution. ALT 2005: 429-443
52	EE	Vladimir Vovk: Defensive Prediction with Expert Advice. ALT 2005: 444-458
51	EE	Vladimir Vovk, Ilia Nouretdinov, Akimichi Takemura, Glenn Shafer: Defensive Forecasting for Linear Protocols. ALT 2005: 459-473
50	EE	Vladimir Vovk, Akimichi Takemura, Glenn Shafer: Defensive forecasting CoRR abs/cs/0505083: (2005)
49	EE	Vladimir Vovk: Non-asymptotic calibration and resolution CoRR abs/cs/0506004: (2005)
48	EE	Vladimir Vovk, Ilia Nouretdinov, Akimichi Takemura, Glenn Shafer: Defensive forecasting for linear protocols CoRR abs/cs/0506007: (2005)
47	EE	Vladimir Vovk: Competitive on-line learning with a convex loss function CoRR abs/cs/0506041: (2005)
46	EE	Vladimir Vovk: On-line regression competitive with reproducing kernel Hilbert spaces CoRR abs/cs/0511058: (2005)
45	EE	Vladimir Vovk: Competing with wild prediction rules CoRR abs/cs/0512059: (2005)
44	EE	Yuri Kalnishkan, Vladimir Vovk, Michael V. Vyugin: How many strings are easy to predict? Inf. Comput. 201(1): 55-71 (2005)
2004
43	EE	Yuri Kalnishkan, Vladimir Vovk, Michael V. Vyugin: A Criterion for the Existence of Predictive Complexity for Binary Games. ALT 2004: 249-263
42	EE	Alexander Gammerman, Yuri Kalnishkan, Vladimir Vovk: On-line Prediction with Kernels and the Complexity Approximation Principle. UAI 2004: 170-176
41	EE	Vladimir Vovk: A Universal Well-Calibrated Algorithm for On-line Classification. Journal of Machine Learning Research 5: 575-604 (2004)
40	EE	Yuri Kalnishkan, Volodya Vovk, Michael V. Vyugin: Loss functions, complexities, and the Legendre transformation. Theor. Comput. Sci. 313(2): 195-207 (2004)
2003
39	EE	Ilia Nouretdinov, Vladimir Vovk: Criterion of Calibration for Transductive Confidence Machine with Limited Feedback. ALT 2003: 259-267
38	EE	Vladimir Vovk: Well-Calibrated Predictions from Online Compression Models. ALT 2003: 268-282
37	EE	Vladimir Vovk: Universal Well-Calibrated Algorithm for On-Line Classification. COLT 2003: 358-372
36	EE	Yuri Kalnishkan, Vladimir Vovk, Michael V. Vyugin: How Many Strings Are Easy to Predict? COLT 2003: 522-536
35		Vladimir Vovk, Ilia Nouretdinov, Alexander Gammerman: Testing Exchangeability On-Line. ICML 2003: 768-775
34	EE	Vladimir Vovk, Glenn Shafer, Ilia Nouretdinov: Self-calibrating Probability Forecasting. NIPS 2003
2002
33	EE	Vladimir Vovk: Asymptotic Optimality of Transductive Confidence Machine. ALT 2002: 336-350
32	EE	Harris Papadopoulos, Kostas Proedrou, Volodya Vovk, Alexander Gammerman: Inductive Confidence Machines for Regression. AMAI 2002
31	EE	Kostas Proedrou, Ilia Nouretdinov, Volodya Vovk, Alexander Gammerman: Transductive Confidence Machines for Pattern Recognition. AMAI 2002
30	EE	Harris Papadopoulos, Kostas Proedrou, Volodya Vovk, Alexander Gammerman: Inductive Confidence Machines for Regression. ECML 2002: 345-356
29	EE	Kostas Proedrou, Ilia Nouretdinov, Volodya Vovk, Alexander Gammerman: Transductive Confidence Machines for Pattern Recognition. ECML 2002: 381-390
28	EE	Vladimir Vovk: On-Line Confidence Machines Are Well-Calibrated. FOCS 2002: 187-196
27		Harris Papadopoulos, Vladimir Vovk, Alexander Gammerman: Qualified Prediction for Large Data Sets in the Case of Pattern Recognition. ICMLA 2002: 159-163
26		Alexander Gammerman, Volodya Vovk: Prediction algorithms and confidence measures based on algorithmic randomness theory. Theor. Comput. Sci. 287(1): 209-217 (2002)
2001
25	EE	Yuri Kalnishkan, Michael V. Vyugin, Volodya Vovk: Loss Functions, Complexities, and the Legendre Transformation. ALT 2001: 181-189
24	EE	Ilia Nouretdinov, Volodya Vovk, Michael V. Vyugin, Alexander Gammerman: Pattern Recognition and Density Estimation under the General i.i.d. Assumption. COLT/EuroCOLT 2001: 337-353
23	EE	Thomas Melluish, Craig Saunders, Ilia Nouretdinov, Volodya Vovk: Comparing the Bayes and Typicalness Frameworks. ECML 2001: 360-371
22		Ilia Nouretdinov, Thomas Melluish, Volodya Vovk: Ridge Regression Confidence Machine. ICML 2001: 385-392
21	EE	Eiji Takimoto, Akira Maruoka, Volodya Vovk: Predicting nearly as well as the best pruning of a decision tree through dynamic programming scheme. Theor. Comput. Sci. 261(1): 179-209 (2001)
20	EE	V. G. Vovk: Probability theory for the Brier game. Theor. Comput. Sci. 261(1): 57-79 (2001)
2000
19	EE	Craig Saunders, Alexander Gammerman, Volodya Vovk: Computationally Efficient Transductive Machines. ALT 2000: 325-333
1999
18		Volodya Vovk, Alexander Gammerman, Craig Saunders: Machine-Learning Applications of Algorithmic Randomness. ICML 1999: 444-453
17		Craig Saunders, Alexander Gammerman, Volodya Vovk: Transduction with Confidence and Credibility. IJCAI 1999: 722-726
16		Alexander Gammerman, Vladimir Vovk: Kolmogorov Complexity: Sources, Theory and Applications. Comput. J. 42(4): 252-255 (1999)
15		Vladimir Vovk, Alexander Gammerman: Complexity Approximation Principle. Comput. J. 42(4): 318-322 (1999)
14		V. G. Vovk: Derandomizing Stochastic Prediction Strategies. Machine Learning 35(3): 247-282 (1999)
1998
13	EE	V. G. Vovk, Chris Watkins: Universal Portfolio Selection. COLT 1998: 12-23
12		Craig Saunders, Alexander Gammerman, Volodya Vovk: Ridge Regression Learning Algorithm in Dual Variables. ICML 1998: 515-521
11		V. G. Vovk: A Game of Prediction with Expert Advice. J. Comput. Syst. Sci. 56(2): 153-173 (1998)
1997
10		V. G. Vovk: Probability Theory for the Brier Game. ALT 1997: 323-338
9	EE	V. G. Vovk: Derandomizing Stochastic Prediction Strategies. COLT 1997: 32-44
8		Volodya Vovk: Competitive On-line Linear Regression. NIPS 1997
7		V. G. Vovk: Learning about the Parameter of the Bernoulli Model. J. Comput. Syst. Sci. 55(1): 96-104 (1997)
1996
6	EE	V. G. Vovk: Learning an Optimal Decision Strategy in an Influence Diagram with Latent Variables. COLT 1996: 110-121
1995
5	EE	V. G. Vovk: A Game of Prediction with Expert Advice. COLT 1995: 51-60
4		V. G. Vovk: Minimum description length estimators under the optimal coding scheme. EuroCOLT 1995: 237-251
1994
3	EE	V. G. Vovk: An Optimal-Control Application of Two Paradigms of On-Line Learning. COLT 1994: 98-109
1992
2		V. G. Vovk: Universal Forecasting Algorithms Inf. Comput. 96(2): 245-277 (1992)
1990
1	EE	V. G. Vovk: Aggregating Strategies. COLT 1990: 371-386

Coauthor Index

1	Alex Gammermam	[74]
2	Alexander Gammerman (Alex J. Gammerman)	[12] [15] [16] [17] [18] [19] [24] [26] [27] [29] [30] [31] [32] [35] [42] [56] [68] [69]
3	Yuri Kalnishkan	[25] [36] [40] [42] [43] [44] [76]
4	Akira Maruoka	[21]
5	Thomas Melluish	[22] [23]
6	Ilia Nouretdinov	[22] [23] [24] [29] [31] [34] [35] [39] [48] [51] [54]
7	Harris Papadopoulos	[27] [30] [32] [74]
8	Kostas Proedrou	[29] [30] [31] [32]
9	Craig Saunders	[12] [17] [18] [19] [23]
10	Glenn Shafer	[34] [48] [50] [51] [73] [77]
11	Akimichi Takemura	[48] [50] [51]
12	Eiji Takimoto	[21]
13	Michael V. Vyugin	[24] [25] [36] [40] [43] [44] [76]
14	Chris Watkins	[13]
15	Fedor Zhdanov	[78]

Colors in the list of coauthors