245 research outputs found
Best-of-Both-Worlds Algorithms for Partial Monitoring
This study considers the partial monitoring problem with -actions and
-outcomes and provides the first best-of-both-worlds algorithms, whose
regrets are favorably bounded both in the stochastic and adversarial regimes.
In particular, we show that for non-degenerate locally observable games, the
regret is in the
stochastic regime and in the
adversarial regime, where is the number of rounds, is the maximum
number of distinct observations per action, is the minimum
suboptimality gap, and is the number of Pareto optimal actions.
Moreover, we show that for globally observable games, the regret is
in the
stochastic regime and in the adversarial regime, where is a
game-dependent constant. We also provide regret bounds for a stochastic regime
with adversarial corruptions. Our algorithms are based on the
follow-the-regularized-leader framework and are inspired by the approach of
exploration by optimization and the adaptive learning rate in the field of
online learning with feedback graphs.Comment: 31 page
Stability-penalty-adaptive Follow-the-regularized-leader: Sparsity, Game-dependency, and Best-of-both-worlds
Adaptivity to the difficulties of a problem is a key property in sequential
decision-making problems to broaden the applicability of algorithms.
Follow-the-Regularized-Leader (FTRL) has recently emerged as one of the most
promising approaches for obtaining various types of adaptivity in bandit
problems. Aiming to further generalize this adaptivity, we develop a generic
adaptive learning rate, called Stability-Penalty-Adaptive (SPA) learning rate
for FTRL. This learning rate yields a regret bound jointly depending on
stability and penalty of the algorithm, into which the regret of FTRL is
typically decomposed. With this result, we establish several algorithms with
three types of adaptivity: sparsity, game-dependency, and Best-of-Both-Worlds
(BOBW). Sparsity frequently appears in real-world problems. However, existing
sparse multi-armed bandit algorithms with -arms assume that the sparsity
level is known in advance, which is often not the case in real-world
scenarios. To address this problem, with the help of the new learning rate
framework, we establish -agnostic algorithms with regret bounds of
in the adversarial regime for rounds, which matches
the existing lower bound up to a logarithmic factor. Meanwhile, BOBW algorithms
aim to achieve a near-optimal regret in both the stochastic and adversarial
regimes. Leveraging the new adaptive learning rate framework and a novel
analysis to bound the variation in FTRL output in response to changes in a
regularizer, we establish the first BOBW algorithm with a sparsity-dependent
bound. Additionally, we explore partial monitoring and demonstrate that the
proposed learning rate framework allows us to achieve a game-dependent bound
and the BOBW simultaneously.Comment: 30 page
Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds
Follow-The-Regularized-Leader (FTRL) is known as an effective and versatile
approach in online learning, where appropriate choice of the learning rate is
crucial for smaller regret. To this end, we formulate the problem of adjusting
FTRL's learning rate as a sequential decision-making problem and introduce the
framework of competitive analysis. We establish a lower bound for the
competitive ratio and propose update rules for learning rate that achieves an
upper bound within a constant factor of this lower bound. Specifically, we
illustrate that the optimal competitive ratio is characterized by the
(approximate) monotonicity of components of the penalty term, showing that a
constant competitive ratio is achievable if the components of the penalty term
form a monotonically non-increasing sequence, and derive a tight competitive
ratio when penalty terms are -approximately monotone non-increasing. Our
proposed update rule, referred to as \textit{stability-penalty matching}, also
facilitates constructing the Best-Of-Both-Worlds (BOBW) algorithms for
stochastic and adversarial environments. In these environments our result
contributes to achieve tighter regret bound and broaden the applicability of
algorithms for various settings such as multi-armed bandits, graph bandits,
linear bandits, and contextual bandits
Large-N reduction for N=2 quiver Chern-Simons theories on S^3 and localization in matrix models
We study reduced matrix models obtained by the dimensional reduction of N=2
quiver Chern-Simons theories on S^3 to zero dimension and show that if a
reduced model is expanded around a particular multiple fuzzy sphere background,
it becomes equivalent to the original theory on S^3 in the large-N limit. This
is regarded as a novel large-N reduction on a curved space S^3. We perform the
localization method to the reduced model and compute the free energy and the
vacuum expectation value of a BPS Wilson loop operator. In the large-N limit,
we find an exact agreement between these results and those in the original
theory on S^3.Comment: 46 pages, 11 figures; minor modification
Improved scientific ballooning applied to the cryo-sampling experiment at Syowa Station
On January 3, 1998, a large balloon (30000 m^3) was successfully launched at Syowa Station for the cryo-sampling of the stratospheric atmosphere. The sampling system splashed down in the Liitzow-Holm Bay and recovered by icebreaker SHIRASE. The cryo-sampling at Antarctica was the first trial in the world and the recovery of a heavy payload was also the first challenge at Syowa Station. A lot of new ballooning technologies were applied to this operation, such as compact balloon launching equipments, a reliable recovery system, a handy ground radio station for the balloon tracking and data acquisition and so forth. The realtime flight data could be received at National Institute of Polar Research (NIPR) in Tokyo by using the computer network via INMARSAT. At NIPR the collaboration members could monitor the entire process of the experiment at Syowa Station in detail and send some instructions and advice. This balloon experiment showed an extended possibility of a large scale scientific ballooning at Syowa Station. This paper deals with those newly developed balloon engineering technologies
Studies on the Tolerance of Grape Vines to Potassium Chlortate. : (I). On the Differences of Tolerance to Potassium Chlolate among the Varieties(1).
1.葡萄の穂品種11種及び台品種4種について栽培実験することなく,それらの葉のKClO3抗毒性の大小によって耐乾性の強弱または少なくともILJINのいうDesciccation Resistanceの強弱を推定する目安を得る目的で本実験を行った.8月下旬から10月下旬にわたり,午後3時頃採葉したものを直ちに0.03%を標準とするKClO3液に挿し,24時間暗所に置いた後,清水に替えて明所に24~72時間置いて葉面に現われる害徴を判定した.2.穂品種の害徴度指数をみるとMuscat of Alexandriaは0,甲州,Neo Muscat及びMuscat Bailey Aは10~11,Campbell Early,巨峰,甲州3尺及びGros Colmanは17~20であった.DelawareはCampbell Earlyよりも抗毒性やや強く,Red MillenniumではMuscat Bailey Aより稍弱い.3.Berlandieri×Riparia 420AはCampbell Earlyよりも抗毒性弱く,Hybrid Francは甲州と同程度である.Riparia×Rupestris 3306は同3309より抗毒性がやや弱い.本実験の範囲内では葡萄の穂品種間ではそれらの耐乾性の強弱とKClO3抗毒性の大小と比例するが,台品種間では逆に比例するものゝ如くである.4.同じく東洋系欧州種に属するといわれる甲州と甲州3尺において後者は前者よりはるかに抗毒性が小であること,及びMuscat of Alexandria種と甲州3尺の交配種であるNeo Muscatの抗毒性が両者の中間であることなどは注目に値する.5.同一樹上の葉相互間にもKClO3抗毒性に個体差が認められる
Intercellular exchange of Wnt ligands reduces cell population heterogeneity during embryogenesis
Wnt signaling is required to maintain bipotent progenitors for neural and paraxial mesoderm cells, the neuromesodermal progenitor (NMP) cells that reside in the epiblast and tailbud. Since epiblast/tailbud cells receive Wnt ligands produced by one another, this exchange may average out the heterogeneity of Wnt signaling levels among these cells. Here, we examined this possibility by replacing endogenous Wnt3a with a receptor-fused form that activates signaling in producing cells, but not in neighboring cells. Mutant mouse embryos show a unique phenotype in which maintenance of many NMP cells is impaired, although some cells persist for long periods. The epiblast cell population of these embryos increases heterogeneity in Wnt signaling levels as embryogenesis progresses and are sensitive to retinoic acid, an endogenous antagonist of NMP maintenance. Thus, mutual intercellular exchange of Wnt ligands in the epiblast cell population reduces heterogeneity and achieves robustness to environmental stress
Establishment of Neurospora crassa as a model organism for fungal virology
The filamentous fungus Neurospora crassa is used as a model organism for genetics, developmental biology and molecular biology. Remarkably, it is not known to host or to be susceptible to infection with any viruses. Here, we identify diverse RNA viruses in N. crassa and other Neurospora species, and show that N. crassa supports the replication of these viruses as well as some viruses from other fungi. Several encapsidated double-stranded RNA viruses and capsid-less positive-sense single-stranded RNA viruses can be experimentally introduced into N. crassa protoplasts or spheroplasts. This allowed us to examine viral replication and RNAi-mediated antiviral responses in this organism. We show that viral infection upregulates the transcription of RNAi components, and that Dicer proteins (DCL-1, DCL-2) and an Argonaute (QDE-2) participate in suppression of viral replication. Our study thus establishes N. crassa as a model system for the study of host-virus interactions. The fungus Neurospora crassa is a model organism for the study of various biological processes, but it is not known to be infected by any viruses. Here, Honda et al. identify RNA viruses that infect N. crassa and examine viral replication and RNAi-mediated antiviral responses, thus establishing this fungus as a model for the study of host-virus interactions
- …